An Investigation on Effective Factors on Share of Agricultural Sector in GDP of Iranian Economy

Size: px
Start display at page:

Download "An Investigation on Effective Factors on Share of Agricultural Sector in GDP of Iranian Economy"

Transcription

1 Ierol Reserch Jourl of ppled d Bsc Sceces 03 vlble ole ISS 5-838X / Vol, 7 (3): Scece xplorer Publcos Ivesgo o ffecve Fcors o Shre of grculurl Secor GDP of Ir coomy Sed khodbkhshzdeh*,morez spr. MSc coomcs Sceces, Mgeme Reserch Ceer, Hormozg Uversy Of Medcl Sceces, Bdr bbs, Ir. MSc grculurl coomcs, Uversy of Ss d Bluches Correspodg uhor: Sed khodbkhshzdeh BSTRCT: Ths reserch lyzes how produco m fcors d relve prces ffec grculurl secor shre gross domesc produco. Suborde feures of gross domesc produco, bsed o Dx d orm s hercl models were used ulzg me seres d durg for deermg effecve fcors o grculurl secor shre GDP. VCM mehod ws used for ssessg equos d exmg log-erm relo bewee vrbles. M resuls of reserch mply he presece of posve effec of prce of grculurl producs o grculurl secor shre GDP log me. The resuls show he mporce of relve prces, becuse, crese he prces of grculurl producs leds o mproveme of exchge relo he fvor of grculure d cuses frmers come fmles. The goverme should eforce he polces of frmer suppor gs decrese of her come. ddolly, of oher resuls of he reserch, verse relo bewee socks ech work force ues d grculure shre GDP c be meoed, becuse, echologcl chge ffecs grculurl secor. Ths resul s cosse wh heorem. Becuse dom echology grculurl secor of Ir hs bee effecve o someexe. Ths my be due o low power, sock cpl vrble effec o grculurl secor shre. Keywords: grculure shre of GDP- Relve prces- grculure- VCM model ITRODUCTIO coomc developme lerure bou he mporce d role of grculure ecoomc developme hs bee lked bou much. he begg of ecoomc developme, grculure s ssoced wh decrese he shre of grculure GDP, he grculurl secor s he lrges secor he ecoomy of developg coures d my be preseed vrous wys such s, cpl, rw merls d chep food supply, mrke for goods mufcured he dusrl secor d provdg foreg exchge o corbue o ecoomc developme (f, 00). There re wo perspecves o he evoluo of ecoomc developme. The rdol vew of developme ecoomss of he 950s d 960s, he growh of grculure, dusry d power dusry sss. I he course of grculure, ecoomy d dusry o he pssve d cve prs of he ecoomy. The secod pproch ws bsed o he heory of Johso d. I ws cler h he role of grculure developme s o oly egve bu lso fve of ecoomc resrucurg developg coures s mpor corbuo grculure c, cpl, foreg exchge d food dusry secors d provde mrke for he producs domesc dusrl creed ( Kerm &Hosey, 003). Idusrl developme mos developed coures, dcg he fc h he grculurl secor, he developme of echology hs secor d s reled dusres frs sep he dusrlzo process of he coury. The dom corbuo o he ecoomc developme of he grculurl secor over he dusrl d servces secors hve bee reduced, d hereforehe relve corbuo of grculure ore (Korkezhd &f, 008). Hsorcl evdece shows h grculurl growh my cses s o ecourge d promoe ecoomc growh. Ths posve reloshp o oly urope d orh merc he erly sges of dusrl developme s d frc coures s hey fd, bu s lso foud Tw d Id.yers. I he sme perod, of he 7 coures wh GDP growh below 3 per ce growh grculure ws oly oe perce or less. To recogze he corbuo of grculure o ecoomc growh, s mpor o kow why he rso process grculure, he shre of grculurl GDP o ol GDP hs decled. Perspecve o he growh of grculurl produco s smuled by growh demd for producs. Sce experece shows h he come elscy for grculurl producs s less h uy, he growh demd for grculurl producs s less h reveue growh (Hosey, 005). Log-erm ecoomc growh s geerlly ssoced wh

2 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 chges he corbuos of ecoomc produco. My reserchers he process of ecoomc growh d drmc rso from grculure o oher secors of he ecoomy hve poed ou (derso, 987). Lews's (953) heory of ecoomc developme o surplus dul- secor model of ecoomc growh hrough he rsfer of relvely from rdol grculure o moder cpls secor would be esfed d expded. ccordg o Lews, he work doe rdol grculure ulmed supply " mes h o reduco grculurl produco, would be se sde (he fl produc s close o zero). Lous, grculure h dusry ws less effecve, log-erm ecoomc oulook s cosse wh he belef h Smh d Rcrdo beg (Mr d Mr, 00). yrvykr rso from rdol grculure o dusry d servces secors does o me h grculurl growh. Mr d Mr smple of 50 coures wh dffere come levels bewee 967 d 99 foud h producvy growh grculure h dusry hs bee fser. However, oed h he process of echcl chge grculure mes h he shre of grculure ol oupu decled (Lg Su, 00). derso (987 ), he resos for he decle he shre of grculure developg ecoomes surveyed. He oed h he decle he shre of grculure GDP for he ecoomy of resrced d smll, he chge echology d he expso of cpl smuleously led o cresed ecoomc effcecy o-grculure (dusry) d come wll cuse cresed reveue lw prses, 's corbuo less of come s spe o food c be sd o hve chged he erms of rde gs grculure 's shre of GDP, d he relve mers decreses (derso,987h). mog he sudes h hve bee doe he feld of he sudy of he Shg (008) s he relve decle he shre of grculure Ch " med. Shg red o fluece hree m fcors: ) prce b) Iveory chges of fcors of produco c) echologcl chge o he relve decle of grculure s shre of Ch's GDP expl. I hs sudy, usg he heorecl model proposed by come d orm (980 ), usg OLS o esme ecoomerc models of pyme. The resuls showed h oly relve prces re sgfc d hve posve effec o he shre of grculure Ch. Icrese he relve prce of grculure o crese he shre of grculure GDP s Ch. Su d collegues (007) sudy eled ccoug reduce grculure s corbuo o ecoomc growh Tw " o exme he fluece of relve prces, veory, produco fcors d echology chge o grculure 's shre of GDP pd. Usg he properes of her GDP o he bss of heorecl models d orm (980) were used. The resuls of he lyss of he resos for he chges Tw's ecoomy s well l. Resuls showed h relve prces, bu lle posve mpc o he shre of grculure GDP he log erm d shor erm. Puysvesv d Kuhd (00), sudy eled " Reducg grculure developg coures: cse sudy of Thld " he grculurl prcg polces mpc, physcl cpl d hum cpl he grculurl secor's shre of GDP corbued o hs rcle log-ru srucurl reloshp bewee he shre of he grculurl secor d s deerms defed. The resuls showed h prcg polces re effecve s grculurl xes, ply prome role he erly developme sges d ler sges re offse. The ccumulo of physcl d hum cpl re mpor. gel s lw d echologcl chges, mog oher secors hs relvely lle effec. Mr d Wre (993), sudy eled " The relve decle he shre of grculure Idoes, lyss of supply-sde " fcors ffecg he shre of grculure GDP beg. They show how hs flueces he fesbly of usg dul mehods d rslog fuco form s lso wdely used grculure, mcroecoomc lyss. Resuls showed h relve prces re of gre mporce he Idoes ecoomy d echologcl chge c be effecve reducg he shre of he grculurl secor. Gk d ygrse (983), o evlue he corbuo of he grculurl secor developg coures, ecoomc growh, Kuzes formul by dvdg he come group of developg coures o hree cegores: low, medum, hgh d of sscs foud h: - he shre of grculure GDP growh d reduco he fl sges of developme s smll. - ro of ogrculurl GDP grculurl secor d chges he relve degree of ecoomc developme of developg coures s lrger. 3 - o-grculurl secor growh re hgher h he growh re of he grculurl secor. Smd (000), reserch eled "The corbuo of grculure o GDP dd. Hs per of Kuzes (964) d proposed les Gk d ygrse yers, usg d from 996 o 965 o sudy he corbuo of hs secor he developme process of he coury d oher OPC coures py. The resuls of hs sudy dce he mpor role of grculure ecoomc developme processes OPC coures, especlly Ir. Fh (994) usg he formul provded by Kuzes d use of sscl formo used he yers 96 o 99 o exme he role of grculure ecoomc developme Ir pymes. The resuls showed h: he shre of grculure hs perod cresed d he shre of o-grculurl secor hs decled. grculurl secor growh of o-grculurl secor growh s lrger. o- grculurl secor s lower h he egve. Removg he ol secor of he ecoomy, he shre of grculure ol vlue dded he se of he ecoomy s cresgly cosdered o be reducg. Removg ol d servce secors of he ecoomy, he shre of grculure vlue dded cresed. Sbbgh Kerm, H. (005), sudy led " ffecs of growh he ecoomy " o lyze how chges relve prces of fcors of produco d he growh of vlue dded secors of he ecoomy d he erreloshps bewee he evelope chrcerscs of he gross 035

3 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 domesc defco of fcors ffecg growh d developme of grculure, dusry d mg servces hey used. Resuls showed h cresg he oupu d effcecy of produco fcors, he prmry fcors of produco wll deped o how well he pplco. Prmeer esmo resuls d elscy s of supply d producvy vrous secors h bewee grculure d oher secors of he ecoomy he use of produco fcors hve srog es here. Gve he bove, cludg he fcors h fluece he ecoomc secors GDP growh, he prces of mufcured goods d vesme ecoomc secors. Due o lmed producve resources d ulmed ws of hum socey whou prces s oe of he effecve ools o lloce resources o vrous ecoomc cves. Chges he prces of mufcured goods secors he cpl mobly bewee dffere secors of he ecoomy. So mos of s pr of he erms of rde s fvor d o rc cpl (Kork ezd &f, 009). Fds. The prce dex for dusrl d servces secors h he grculurl prce dex durg hs perod eded o hve cresed o greer exe (Hosse, 005). Ths sudy uses ul d for he perod 340 o 386 d he ecoomy usg ecoomerc echques, vecor error correco model VCM, your log erm reloshp or reloshps bewee vrbles he model were esmed. lso how relve prces, blce of produco d echcl chge he shre of grculure GDP ws lyzed. MTHODS ul d o he grculurl secor s shre of ol ccous for he perod 340 o 390 colleced by he Cerl Bk of Ir (les d vlble) ws. The m fcors of produco such s ld d (R), (L) d cpl (K ), respecvely, from he FO webse, he webse ws obed from he Sscl Ceer of Ir 's Cerl Bk webse.he gross pr s bsed o heorecl models d orm (980) were used. Geerl form of hese models re he frs wo prs of grculurl produco () d o () d hree pus () erms of where he J =, d vecors pus clude cer pus J d kg pr geerl fcors such s he ecoomy s. Woodld (98 ), he gross domesc (GDP) ws defed s he overll ecoomy. G( P, P, V, V, V, ) Mx x{ P. Y ( V, V, ) P. Y ( V, V, )} X {( V, V, V, V ) : V V, V V, V V V } P. Y ( V, V, ) P. Y ( V, V, ) : V V, V V, V V,, } Mx{ G( P, P, V, V, V, ) g ( P, V *, V, ) g ( P, V *, V, The fuco reurs poro of GDP, whch uder cer rules d codos, defes echologes (Dyour, 974). Ths produco fuco s homogeeous of degree oe ll prces d veory fcors ( * V V ) d hs he sme chrcerscs fuco of he ol GDP of he ecoomy. Fuco d s specfc *, fucol form (rslog fuco) shres by oprmerc lyss of vrous fcors (prce, veory of pus d producvy of fcors of produco) s he produco of (Kohl, 994). The blce of cer echology for opml resource lloco bewee grculure d o-grculurl ecoomy bes poso depeds o he relve prces of producs re possbles froer. Impc o mxmze profs, compeve equlbrum c be see s soluo o he problem of mxmzg reveue suscepble o echology, veory d erl fcors vecor ech sep of deermg prces of cer producs. ssumg h T () s he probbly fuco of he me s deermed o be publc fgure GDP fuco wh respec o he me vrble, he GDP showed s follows (Kohl, ; Woodld, 977). ) Y GDP ( P, X, ) mx { P. y : ( y, X ) T ( )} y Vecoryso h he fl goods,.e. grculurl produco () d he o-grculurl producs()we show. Pvecor of prces of fl goods d o-grculurl producs s, X s vecor of supply fcors of produco, cludg (L),cpl(K) d resources(r)s, T () of covex se, d (me) s useds proxy for echcl chge. Becuse of cos reurs o scle produco fucos re fucos of GDP c bese gs come from fcors of produco. ^ Y GDP( p = p, p * *. y p. y, L, K) 036

4 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 = w. L r. K = W ( p, p ) L R( p, p K ) Trslog produco fuco ws used o demosre he GDP. Tr slog fuco provdes ll he feures of he eoclsscl produco fuco. Tr slog produco fuco shows hree res where he mrgl producs olveor egve(dyyvr, 974). These forms reflec possble dffereces erms of produco d mgeme re lso beer. Trs log fuco for model of he geerl form of hs fuco, he followg prmeers re flexble, re used. L( Y) L( x ) ( Lx ) ( Lx )( Lx I he bove equo, X represes fcor of produco, α d β prmeers of he model d he dex s dffere fcors of produco. I s derved s follows. L( Y ) Y ( ( Lx ) ( Lx ))( ) L( x ) x Gve he rslog fucol form whou he subscrp, he GDPs s follows: lg 0 l P l P l X h l P,Commody prces d X h l P l P h l X l X ) k k l X l X ques of produco fcors d represe me. Followg resrcos for he properes o ssfy he eoclsscl produco heory, he prmeers of he model were cosdered. h k k,,, 0 h 0, 0 h,, h k k Due o helmosdcodosecessryomxmzeproduco,hefuco of he logrhm of he ro of prces of grculurl GDP, he shre of grculure GDP, ccordg o he followg reloshps were developed. LG G p p y p. Lp S S S ( )( ) y ( ) S.= p G G G h Lp l P h Lp Lp Lx h h h ( quo(5) c be rewre. S )l P l Lx l L k l K ( 0 l( P / P ) l( K / L) l( R / L) 3 l k ) l R ccordg o he equo, he shre of grculure, he chges c bedemosreds follows: S l( P P ) l( K L) l( R L) 3 For perod of dscouous chge he shre of grculure GDP, relve prce chges, chges he cpl sock, chges crege of produco d chges echology. Iclo d dreco of echologcl chge wh cos relve prces, he chge he shre s mesured. grculure's shre of k 037

5 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 he esmed prmeers of he equo, we c ob he reloshp bewee echologcl chges s follows. LG G p x The frs compoe shows h pure echologcl chge, o cler reloshp wh producvy d relve prces of fcors of produco, d o fuco, s s cosdered pr of he cos or ercep d crese or decrese he equo rsm corbuo owrds he boom d op. Whe hs compoe s egve, dcg h he corbuo of grculure o he equo of rsfer s low, reflecg echologcl developmes. The secod compoe shows how he erply of fcors o ech oher over me. I oher words, chges echology over me, wh effec hs hd o ges. Replcg he cuse or cuses of he fcors h hs led o svgs? The hrd compoe, dcg h he cpcy of he frm's echcl developmes, wh effec hs. I s cler h echcl developmes o expd he scle of produco, hereby beefg from ecoomes resulg from cresed produco (yl K, 997). Techologcl chge my be skewed owrds he produco pus. I cse of echcl progress, mesure he dgol suos re: I b S Hvg he requred d, we esme he equo wh respec o he shre of grculure GDP usg VCM fsdsy should be ke. Possble o express log-erm reloshp bewee he vrbles he model es, " Johsso " o esme he umber of log- ru covergece vecors d he lkelhood ro es (mxmum ge vlue es d rce es) ws used o deec he umber of vecors coverge. There s covergece bewee se of ecoomc vrbles, bsed o he models provded correc. flucuo he shor ru error correco model (shor-erm mblces) vrbles o vlues s log erm reloshp. gel d Grger beleves h every log erm reloshp, shor-erm model s o cheve equlbrum esurg MC d vce vers (ufresy, 009). Boys d Sh (996), he pper showed h he CM loe c sy wheher or o here s log-ru reloshp bewee he vrbles. Ths mes h he vlue of () CM bewee zero d mus oe f he model s equl o he egve log-ru reloshp exss d f ws, would be megless f s smller h he egve oe, here s o log-ru reloshp (Teshky, 006). The coeffce of error, speed of dusme owrds log-ru equlbrum shows (uferesy, 009). RSULTS D DISCUSSIO Regressos volvg o sory vrbles, cusg regresso re flse, herefore, he vrbles he model o ssess wheher he vrbles re sory or o esed. Soryo dgose or re o sory he me seres u roo ess were used (Slk, 385). The resuls of he bove ess boh wh d whou he red Tble re gve. Qufed by comprg he es ssc d he crcl vlue sgfcce level of 5% s observed provded h he vrble shre of grculure GDP, relve prces of lbor d cpl per u of ld h, he bsolue vlue of he es ssc Dckey - Fuller geerlzed (DF) of he bsolue vlue s less h he crcl vlue. Thus, he u roo ull hypohess co be reeced bsed o he resuls of he me seres of ech vrble s o sory. fer vrbles were deermed 95% cofdece level, o exme he me-seres vrbles re egred of wh ws dscussed. For he frs cou he seres, whch were defed? Tble summrzes he es resuls Dckey - Fuller geerlzed frs order dfferece of he vrbles shows Frs-order dfferece operor. ccordg o Tble, s observed h he bsolue vlue of ll he vrbles of he bsolue vlue of DF es crcl vlues 5% sgfcce level s lrger. Thus, he u roo ull hypohess s reeced bsed o he resul of he frs order dfferece of sc vrbles d summed degree or zero I (0) hve, hece he vrbles re egred of order oe I() hve. Lke oher ecoomerc models s ssumed h he VR model, he sscl properes re error erms, o provde resoble ssumpo breks vrbles he model should be cosdered. Ths reserch herefore he mxmum mou Schwrz crer - Byes (SBC) usg opml lg ws chose for ech of he vrbles. I geerl, he bove dscussos, ws cocluded h he model vrbles I () hve d use he ecessry covergece Johsso - hs Juselus. Wh he help of hs echque d vecor error correco model c be log-erm d shor-erm reloshps o be deermed model prmeers. Deerme he opml lg legh he model VR, he frs sep log-erm covergece mehod, " Johsso " s. I order o deerme he ppropre lg VR model LR ssc d he kke crero (IC) ws used. Bsed o he crer Tble 3 repors he opml lg 3 ws seleced. Bsed o Johsso - Jusluvs o cheve he rk of co-egro vecors П 038

6 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 mrx o be deermed. Deermed by he rk of he esmed chrcersc roos re cocered. Resuls Tble (4) d (5) shows h o he bss of hese sscs, here s oly oe vecor of log-ru covergece of he Hmbshgy Vecor Tble (6) hve bee repored. So log s he followg regresso expresso. S = / 76+ 0/ 5 LP -0/ 70 LK + 0/ 5076 LR + 0/ 0068 T - 0/ 084 DU57 (- 5/ 4) ( 0/57) (- 7/ 7) (- 6/ 95) ( 3 / 53) The egve sg for he coeffce of he cpl ro - work suggess h here s verse reloshp bewee he shres of grculure GDP. The esmed coeffce for he vrble cpl sock s egve d ssclly sgfc. There s log erm process vrble prmeers q. Ths prmeer dces he relve re of crese oupu d pus. The posve coeffce of he vrble he equo h echcl chge grculure s shre of ol grculurl oupu cresed (dex 0068 / 0) s. Techologcl chge he user's pu s. Therefore, he dom echology he grculurl secor Ir s lrgely mul, d h c cuse low power, vrble effec o he shre of he grculurl secor s cpl. Ir's vesmes grculure so h here s less eed. Ideed, he rrvl of ew echology o replce lbor he grculurl secor, whch my hve egve mpc o grculurl oupu s se. The resuls of he sudy showed compbly ssue hypohesze h he crese veory s fcor, fcor h creses produco d reduces he produco of oher goods. The pr h uses he lrger proporo h mos oher secors of he ecoomy develops. If he oupu of more ppropre seco of he segmes creses, some oher should be reduced (Woodld, 98). The mpc of he dummy vrble reduces he shre of grculure GDP sze 084 / 0 perce s. The shre of grculure GDP equo error correco model resuls Tble 7 hs bee repored. Wh 's mos mpor s he error correco model, cludg error correco coeffce, whch represes he speed of dusme owrds equlbrum he log-erm mblce s. s show Tble (7) s sgfc, he coeffce s sgfc d hs egve sg, so he coeffce of he CM s bewee zero d egve oe d sgfc, log-erm co-egro reloshp bewee vrbles, hs mehod s lso verfed. lso, gve h he coeffce of error correco (CT) s esmed o 03/0- shows per yer, 0 / 0 mblces he shre of grculure GDP durg he perod fer he dusme. So he dusme owrds equlbrum s relvely slow. Tble. Resuls of he ess Dckey-Full ergeerlzed (DF) he cse of model vrbles. Wh ercep d o red Wh ercep d ored vrble The opml umber of The opml umber of DF Crcl vlue lgs lgs DF Crcl vlue S 0 -/ 74 -/ / 884-3/ 506 L(p/p) 0 -/ 363 -/ / 3-3/ 506 L(K/L) 0 -/ 905 -/ / 44-3/ 508 L(R/L) 0 -/ 357 -/ / 433-3/ 55 Source: The resuls of he sudy, expled: Crcl vlues 5% level, d he choce of opml lgs by SIC crer Tble. Resuls of he ess Dckey-Full ergeerlzed (DF) frs dfferecg he model vrbles. Wh ercep d ored Wh ercep d ored vrble The opml umber of The opml umber of DF Crcl vlue lgs lgs DF Crcl vlue S 0-4/ 776 -/ / 86-3/ 508 L(p/p) 0-7/ 3 -/ / 4-3/ 508 L(K/L) 0-7/ 653 -/ / 58-3/ 50 L(R/L) 0-5/ 864 -/ / 8-3/ 58 Source: The resuls of he sudy, expled: Crcl vlues 5% level, d he choce of opmllgs by SIC crer lg 0 3 Tble3. Deermo of he opmllg legh he model VR. LogL LR IC HQ 34/03-6/907-6/ /3509 * 9/ 309 *-3/ 304 *-/ /4074 5/803-3/0940 -/ /656 3/839-3/ /9007 Source: reserch fdgs, expl: *selec he opmllg legh by he sdrdlr, IC, HQ 5% level Tble4. Deerme he umber of log-ermco-egro vecors (λ rce). ull hypohess s sumge rco The effec of he es ssc The crcl level of5% * = 0r r 06/ /8038 r r 5/ /876 r 3r 33/96 4/95 3r 4r 6/939 5/87 4r 5r 7/563 /579 Source: reserch fdgs, expl: *reec he ull hypo hess h here s oco-egro vecor sgfcce level of 5% 039

7 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 Tble5. Deerme he umber of co-egro vecors bsed o he mxmumege vlue es(λ mx). ull hypohess ssumgerco The effec ofhe es ssc The crcllevel of5% * = 0r = r 54/ /330 r = r 7/7447 3/83 r = 3r 7/0303 5/83 3r = 4r 9/3695 9/3870 4r = 5r 7/563 /579 Source: reserch fdgs, expl: *reec he ull hypo hess h here s oco-egro vecor sgfcce level of 5% Vrble S(-) C LP(-) LK(-) LR(-) T DU57(-) Coeffce / / /539 0/703-0/ / /08434 Tble6. vecor vrbles Johsees. Sdrd rror - - 0/039 0/036 0/ / /0387 Source: Reserch Fdgs -ssc /4093 9/ /7790-6/9590 3/5333 Tble7. smo ofvecor error correco model. CM rror Correco D(S) D(LP/P) D(LK/L) D(LR/L) D(DU57) CM(-) -0/03 *(0/0344) 0/935 (0/30) 0/458 (/803) 0/480 (0/954) -0/774 (0/7735) ]**- 3/ 080 [ ] 3 / 0969 [ ] 0 / 3607 [ ] / 457 [ ]- / 0009 [ R-squred 0/4 0/7 0/04 0/4 0/ F-ssc 4/97 /434 0/866 4/00 0/866 kke IC -6/990 -/636 0/0890-3/5075-0/756 Schwrz SC -6/7043 -/3495 0/3757-3/08-0/4694 Source: reserch fdgs oe:*the umbers () resdrd devos ofhe coeffces.*the umbers [] re-sscs of he coeffces. COCLUSIOS D RCOMMDTIOS The esmo resuls dce h he, hve posve mpc o he shre of grculure GDP he log ru. Decle grculurl producvy by reducg he shre of grculure re reled. I ddo, he crese cpl sock per u of lbor, he shre of grculure hs lle relevce. Ths resul s cosse wh he proposo. Therefore, he dom echology he grculurl secor Ir s lrgely mul, d h c cuse low power, he effec of cpl sock vrble s he shre of he grculurl secor. Ivesme he grculurl secor Ir s such h requres less. Ideed, he rrvl of ew echology o replce lbor he grculurl secor, whch my hve egve mpc o grculurl oupu, s se. ccordg o he resuls of hs sudy, he Followg gudeles re suggesed. The resuls showed he mporce of relve prces. The crese of grculurl prces d mproved erms of rde fvor of grculure mkes frmers' comes rse. However, low-come households hs pr of he goverme requre domesc producers gs loss of reveue, come suppor polces for frmers o pply. Goverme polcy o prcg of grculurl producs due o prce creses should be mde oher secors. Gve h he grculurl prce creses mpc o frmers' comes d cuses he erms of rde fvor of grculure d rel come of frmers cresed chge. Due o he cresg role of grculure GDP, cresed vesme he secor d preve he flow of cpl o uproducve secors offered lucrve. Reducg dsoros d flucuos he relve prce of grculurl commodes or oherwse chge he erms of rde fvor of grculure d mufcurg resources o be fueled owrd medo d brokerge cves d servces o be produced. RFRCS brshm J The book Prcples of coomercs, Volume II, Fourh do. Tehr Uversy Press. derso K O Why grculure Decles wh coomc Growh. grculurl coomcs. : Cerl Bk of he Islmc Republc of Ir. coomc repors. Tbles of ol ccous d blce shee. Yers Dewer, Morrso.998. xpor supply d Impor Demd Fucos: Produco Therypproch. I Roder Feesr, ed., mprcl Mehods for Ierol Trde, Cmbrdge, mss.mit. Dx, orm.998. Therory of Ierol Trde. Welwy(gld) d Cmdrdge: J. sbe d Cmbrdge Uversy Press. Fh F The role of grculure ecoomc developme (produco, vesme, employme, foreg exchge). Proceedgs of he Secod Symposum of Ir grculurl polcy. College of grculure, Shrz Uversy. Fu S. 99. ffecs of Techologcl Chge d Isuol Reform o Produco Growh Chese grculure. merc Jourl of grculurl coomc: Ghk S, Igers K grculure d coomc Deveopme. The Joh Hopes Uversy press. 040

8 Il. Res. J. ppl. Bsc. Sc. Vol., 7 (3), , 03 Goph T, Roe.997. Surces of Secorl Growh coomy-wde coex: he Cse of U.S grculure. Jourl of Produchvy lyss. 8: Hrrg J.997. Techology, Fcor Suples, d Ierol Speclzo: smg he eoclsscl Model. The merc coomc Revew. hosseyu R grculurl growh lkges he ecoomy. Ph.D. Dssero. Uversy. P: 4. Kohl U Gross ol Produc Fuco d he Derved Demd for Impors d xpors. Cd Jourl of coomcs, (): Kohl U.99. Techology, Duly, d Foreg Trde: The GP Fuco pproch o Modelg Impors xpors. rbor, MI: Uversy of Mchg Press. korkezhd Zh, kf B. 009,xme he erco bewee secors of he ecoomy wh emphss o he mpor role of grculure. d ecoomc developme. Sxeeh yer. o. 63. korkezhd Zh, kf B Deerme he relve corbuo of ecoomc secors he ecoomy: he use of smulo models, Jourl of grculurl coomcs. () :69-9. Lu Lwrece J, Yoopoulos The Me-Produco Fuco pproch o Techologcl Chge World grculure. Jourl of Developme coomcs. 3:4-69. Mr W, Wrr PG.993. xplg he Relve Decle of grculure: Supply-Sde lyss for Idoes. World Bk coomc Revew 7(3): Mr W, Mr D. 00. Producvy Growh grculure versus mufcurg. coomc Developme d Culurl Chge. 49-: f.38, The role of grculure ecoomc developme of Ir. grculure d ol Developme Coferece. Tehr. Msry of grculure. oferesy.009, U roo d co-egro ecoomercs. Secod edo. Rs ssued. Tehr. Puysvsu C, Coxhed P. 00. O he Decle of grculure Developg coures: Reepreeo of he vdece. Sff Pper Seres Deprme of grculurl & ppled coomcs. Uversy of Wscos Mdso. Sbbgh M. Kerm R, Hosse ffecs growh he ecoomy. grculurl d Developme coomcs. Twelfh yer. o. 45. Smd ssess he corbuo of he grculurl secor he ecoomc growh of Ir d oher OPC coures. Jourl of grculurl d Developme coomcs. Yer 7. o. 6. Shg Y The Relve Decle of grculure ch. MPR Pper o Su L, Fulg L, Peerso W ccug for grculurl Decle Wh coomc Growh Tw. grculurl coomc. 36(): Su L. 00. Idusrl Producvy Growh d Opeess Tw. Workg pper, s Coferece o ffcecy d Producvy Growh. Teshk.006. ppled coomercs usg Mcrof. r Isue debugger. Tehr. Woodld D. 98. Ierol rd d resource lloco. mserdm, orh-holld. World Bk.99. World Developme Repor 99. ew York: Oxford Uversy Press. 04

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X ECON 37: Ecoomercs Hypohess Tesg Iervl Esmo Wh we hve doe so fr s o udersd how we c ob esmors of ecoomcs reloshp we wsh o sudy. The queso s how comforble re we wh our esmors? We frs exme how o produce

More information

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files)

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files) . Iroduco Probblsc oe-moh forecs gudce s mde b 50 esemble members mproved b Model Oupu scs (MO). scl equo s mde b usg hdcs d d observo d. We selec some prmeers for modfg forecs o use mulple regresso formul.

More information

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as.

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as. Lplce Trfor The Lplce Trfor oe of he hecl ool for olvg ordry ler dfferel equo. - The hoogeeou equo d he prculr Iegrl re olved oe opero. - The Lplce rfor cover he ODE o lgerc eq. σ j ple do. I he pole o

More information

Integral Equations and their Relationship to Differential Equations with Initial Conditions

Integral Equations and their Relationship to Differential Equations with Initial Conditions Scece Refleco SR Vol 6 wwwscecereflecocom Geerl Leers Mhemcs GLM 6 3-3 Geerl Leers Mhemcs GLM Wese: hp://wwwscecereflecocom/geerl-leers--mhemcs/ Geerl Leers Mhemcs Scece Refleco Iegrl Equos d her Reloshp

More information

4. Runge-Kutta Formula For Differential Equations

4. Runge-Kutta Formula For Differential Equations NCTU Deprme o Elecrcl d Compuer Egeerg 5 Sprg Course by Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos To solve e derel equos umerclly e mos useul ormul s clled Ruge-Ku ormul

More information

Isotropic Non-Heisenberg Magnet for Spin S=1

Isotropic Non-Heisenberg Magnet for Spin S=1 Ierol Jourl of Physcs d Applcos. IN 974- Volume, Number (, pp. 7-4 Ierol Reserch Publco House hp://www.rphouse.com Isoropc No-Heseberg Mge for p = Y. Yousef d Kh. Kh. Mumov.U. Umrov Physcl-Techcl Isue

More information

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY [Mjuh, : Jury, 0] ISSN: -96 Scefc Jourl Impc Fcr: 9 ISRA, Impc Fcr: IJESRT INTERNATIONAL JOURNAL OF ENINEERIN SCIENCES & RESEARCH TECHNOLOY HAMILTONIAN LACEABILITY IN MIDDLE RAPHS Mjuh*, MurlR, B Shmukh

More information

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula NCTU Deprme o Elecrcl d Compuer Egeerg Seor Course By Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos A. Euler Formul B. Ruge-Ku Formul C. A Emple or Four-Order Ruge-Ku Formul

More information

STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION

STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION The Bk of Thld Fcl Isuos Polcy Group Que Models & Fcl Egeerg Tem Fcl Mhemcs Foudo Noe 8 STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION. ก Through he use of ordry d/or prl deres, ODE/PDE c rele

More information

BEST PATTERN OF MULTIPLE LINEAR REGRESSION

BEST PATTERN OF MULTIPLE LINEAR REGRESSION ERI COADA GERMAY GEERAL M.R. SEFAIK AIR FORCE ACADEMY ARMED FORCES ACADEMY ROMAIA SLOVAK REPUBLIC IERAIOAL COFERECE of SCIEIFIC PAPER AFASES Brov 6-8 M BES PAER OF MULIPLE LIEAR REGRESSIO Corel GABER PEROLEUM-GAS

More information

Unscented Transformation Unscented Kalman Filter

Unscented Transformation Unscented Kalman Filter Usceed rsformo Usceed Klm Fler Usceed rcle Fler Flerg roblem Geerl roblem Seme where s he se d s he observo Flerg s he problem of sequell esmg he ses (prmeers or hdde vrbles) of ssem s se of observos become

More information

An improved Bennett s inequality

An improved Bennett s inequality COMMUNICATIONS IN STATISTICS THEORY AND METHODS 017,VOL.0,NO.0,1 8 hps://do.org/10.1080/0361096.017.1367818 A mproved Bee s equly Sogfeg Zheg Deprme of Mhemcs, Mssour Se Uversy, Sprgfeld, MO, USA ABSTRACT

More information

APPLICATION REGRESSION METHOD IN THE CALCULATION OF INDICATORS ECONOMIC RISK

APPLICATION REGRESSION METHOD IN THE CALCULATION OF INDICATORS ECONOMIC RISK APPLICATIO REGRESSIO METHOD I THE CALCULATIO OF IDICATORS ECOOMIC RISK Ec. PhD Flor ROMA STA Asrc The ojecve of hs Arcle s o show h ecoomc rsk s flueced mulple fcors, d regresso mehod c eslsh he ee of

More information

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25 Modelg d redcg Sequeces: HMM d m be CRF Amr Ahmed 070 Feb 25 Bg cure redcg Sgle Lbel Ipu : A se of feures: - Bg of words docume - Oupu : Clss lbel - Topc of he docume - redcg Sequece of Lbels Noo Noe:

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

Calculation of Effective Resonance Integrals

Calculation of Effective Resonance Integrals Clculo of ffecve Resoce egrls S.B. Borzkov FLNP JNR Du Russ Clculo of e effecve oce egrl wc cludes e rel eerg deedece of euro flux des d correco o e euro cure e smle s eeded for ccure flux deermo d euro

More information

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty S 6863-Hou 5 Fuels of Ieres July 00, Murce A. Gerghy The pror hous resse beef cl occurreces, ous, ol cls e-ulero s ro rbles. The fl copoe of he curl oel oles he ecooc ssupos such s re of reur o sses flo.

More information

Chapter Simpson s 1/3 Rule of Integration. ( x)

Chapter Simpson s 1/3 Rule of Integration. ( x) Cper 7. Smpso s / Rule o Iegro Aer redg s per, you sould e le o. derve e ormul or Smpso s / rule o egro,. use Smpso s / rule o solve egrls,. develop e ormul or mulple-segme Smpso s / rule o egro,. use

More information

Sources of Economic Growth in Japan. and the United States

Sources of Economic Growth in Japan. and the United States Sources of Ecoomc Growh Jp he Ue Ses Heo No Ymg Uversy Kok Kyo Ohro Uversy of Agrculure Veerry Mece Asrc Ths pper ms o exme he ymc feures of he sources of ecoomc growh Jp he Ue Ses. We prese se of Byes

More information

The Infinite NHPP Software Reliability Model based on Monotonic Intensity Function

The Infinite NHPP Software Reliability Model based on Monotonic Intensity Function Id Jourl of Scece d Techology, Vol 8(4), DOI:.7485/js/25/v84/68342, July 25 ISSN (Pr) : 974-6846 ISSN (Ole) : 974-5645 The Ife Sofwre Relly Model sed o Moooc Iesy Fuco Te-Hyu Yoo * Deprme of Scece To,

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

The Existence and Uniqueness of Random Solution to Itô Stochastic Integral Equation

The Existence and Uniqueness of Random Solution to Itô Stochastic Integral Equation Appled Mhemcs,, 3, 8-84 hp://dx.do.org/.436/m..379 Pulshed Ole July (hp://www.scrp.org/jourl/m) The Exsece d Uqueess of Rdom Soluo o Iô Sochsc Iegrl Equo Hmd Ahmed Alff, Csh Wg School of Mhemcs d Iformo

More information

1. Consider an economy of identical individuals with preferences given by the utility function

1. Consider an economy of identical individuals with preferences given by the utility function CO 755 Problem Se e Cbrer. Cosder ecoomy o decl dduls wh reereces e by he uly uco U l l Pre- rces o ll hree oods re ormled o oe. Idduls suly ood lbor < d cosume oods d. The oerme c mose d lorem es o oods

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

Final Exam Applied Econometrics

Final Exam Applied Econometrics Fal Eam Appled Ecoomercs. 0 Sppose we have he followg regresso resl: Depede Varable: SAT Sample: 437 Iclded observaos: 437 Whe heeroskedasc-cosse sadard errors & covarace Varable Coeffce Sd. Error -Sasc

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

Introduction to Neural Networks Computing. CMSC491N/691N, Spring 2001

Introduction to Neural Networks Computing. CMSC491N/691N, Spring 2001 Iroduco o Neurl Neorks Compug CMSC49N/69N, Sprg 00 us: cvo/oupu: f eghs: X, Y j X Noos, j s pu u, for oher us, j pu sgl here f. s he cvo fuco for j from u o u j oher books use Y f _ j j j Y j X j Y j bs:

More information

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type J N Sce & Mh Res Vol 3 No (7) -7 Alble ole h://orlwlsogocd/deh/sr P-Coey Proery Msel-Orlcz Fco Sce o Boher ye Yl Rodsr Mhecs Edco Deree Fcly o Ss d echology Uerss sl Neger Wlsogo Cerl Jdoes Absrcs Corresodg

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3. C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

Chapter Unary Matrix Operations

Chapter Unary Matrix Operations Chpter 04.04 Ury trx Opertos After redg ths chpter, you should be ble to:. kow wht ury opertos mes,. fd the trspose of squre mtrx d t s reltoshp to symmetrc mtrces,. fd the trce of mtrx, d 4. fd the ermt

More information

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

G1-Renewal Process as Repairable System Model

G1-Renewal Process as Repairable System Model G-Reewl Process s Reprble Sysem Model M.P. Kmsky d V.V. Krvsov Uversy of Mryld College Prk USA Ford Moor Compy Derbor USA Absrc Ths pper cosders po process model wh moooclly decresg or cresg ROCOF d he

More information

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead)

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead) Week 8 Lecure 3: Problems 49, 5 Fourier lysis Coursewre pp 6-7 (do look Frech very cofusig look i he Coursewre ised) Fourier lysis ivolves ddig wves d heir hrmoics, so i would hve urlly followed fer he

More information

Chapter Trapezoidal Rule of Integration

Chapter Trapezoidal Rule of Integration Cper 7 Trpezodl Rule o Iegro Aer redg s per, you sould e le o: derve e rpezodl rule o egro, use e rpezodl rule o egro o solve prolems, derve e mulple-segme rpezodl rule o egro, 4 use e mulple-segme rpezodl

More information

A NEW FIVE-POINT BINARY SUBDIVISION SCHEME WITH A PARAMETER

A NEW FIVE-POINT BINARY SUBDIVISION SCHEME WITH A PARAMETER Jourl of ure d Appled Mhemcs: Advces d Applcos Volume 9 Numer ges -9 Avlle hp://scefcdvcesco DOI: hp://dxdoorg/6/ms_9 A NEW FIVE-OINT BINARY UBDIVIION CHEME WITH A ARAMETER YAN WANG * d HIMING LI chool

More information

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

Partial Molar Properties of solutions

Partial Molar Properties of solutions Paral Molar Properes of soluos A soluo s a homogeeous mxure; ha s, a soluo s a oephase sysem wh more ha oe compoe. A homogeeous mxures of wo or more compoes he gas, lqud or sold phase The properes of a

More information

Modified Taylor's Method and Nonlinear Mixed Integral Equation

Modified Taylor's Method and Nonlinear Mixed Integral Equation Uversl Jourl of Iegrl quos 4 (6), 9 wwwpperscecescom Modfed Tylor's Mehod d oler Mxed Iegrl quo R T Moog Fculy of Appled Scece, Umm Al Qurh Uversy Mkh, Kgdom of Sud Ar rmoog_777@yhoocom Asrc I hs pper,

More information

ASYMPTOTIC BEHAVIOR OF SOLUTIONS OF DISCRETE EQUATIONS ON DISCRETE REAL TIME SCALES

ASYMPTOTIC BEHAVIOR OF SOLUTIONS OF DISCRETE EQUATIONS ON DISCRETE REAL TIME SCALES ASYPTOTI BEHAVIOR OF SOLUTIONS OF DISRETE EQUATIONS ON DISRETE REAL TIE SALES J. Dlí B. Válvíová 2 Bro Uversy of Tehology Bro zeh Repul 2 Deprme of heml Alyss d Appled hems Fuly of See Uversy of Zl Žl

More information

Reinforcement Learning

Reinforcement Learning Reiforceme Corol lerig Corol polices h choose opiml cios Q lerig Covergece Chper 13 Reiforceme 1 Corol Cosider lerig o choose cios, e.g., Robo lerig o dock o bery chrger o choose cios o opimize fcory oupu

More information

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions: Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log

More information

Novel Bose-Einstein Interference in the Passage of a Jet in a Dense Medium. Oak Ridge National Laboratory

Novel Bose-Einstein Interference in the Passage of a Jet in a Dense Medium. Oak Ridge National Laboratory Rdge Worksho, INT, My 7-, 0 Novel Bose-Ese Ierferece he Pssge of Je Dese Medu Cheuk-Y Wog Ok Rdge Nol Lborory Our focus: recols of edu ros fer je collso Poel odel versus Fey lude roch Bose-Ese erferece

More information

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS KINEMTICS OF RIGID ODIES RELTIVE VELOCITY RELTIVE CCELERTION PROLEMS 1. The crculr dsk rolls o he lef whou slppg. If.7 m s deerme he eloc d ccelero of he ceer O of he dsk. (516) .7 m s O? O? . The ed rollers

More information

MODELING AND FORECASTING THE TEXTILE PRICE INDEX USING SEMI-NONPARAMETRIC REGRESSION TECHNIQUE

MODELING AND FORECASTING THE TEXTILE PRICE INDEX USING SEMI-NONPARAMETRIC REGRESSION TECHNIQUE Ierol Jourl of Iovve Mgeme Iformo & Produco ISME Ierol c 4 ISSN 85-5455 Volume 5 Numer Mrch 4 PP. 89-98 MODELING ND FORECSTING THE TEXTILE PRICE INDEX USING SEMI-NONPRMETRIC REGRESSION TECHNIQUE JINGHUI

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo

More information

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad

More information

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants Rochester Isttute of echology RI Scholr Wors Artcles 8-00 bocc d ucs Nubers s rdgol trx Deterts Nth D. Chll Est Kod Copy Drre Nry Rochester Isttute of echology ollow ths d ddtol wors t: http://scholrwors.rt.edu/rtcle

More information

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall 8. Queueg sysems lec8. S-38.45 - Iroduco o Teleraffc Theory - Fall 8. Queueg sysems Coes Refresher: Smle eleraffc model M/M/ server wag laces M/M/ servers wag laces 8. Queueg sysems Smle eleraffc model

More information

TEACHERS ASSESS STUDENT S MATHEMATICAL CREATIVITY COMPETENCE IN HIGH SCHOOL

TEACHERS ASSESS STUDENT S MATHEMATICAL CREATIVITY COMPETENCE IN HIGH SCHOOL Jourl o See d rs Yer 5, No., pp. 5-, 5 ORIGINL PPER TECHERS SSESS STUDENT S MTHEMTICL CRETIVITY COMPETENCE IN HIGH SCHOOL TRN TRUNG TINH Musrp reeved: 9..5; eped pper:..5; Pulsed ole:..5. sr. ssessme s

More information

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS Vol.7 No.4 (200) p73-78 Joural of Maageme Scece & Sascal Decso IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS TIANXIANG YAO AND ZAIWU GONG College of Ecoomcs &

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Application of Multiple Exp-Function Method to Obtain Multi-Soliton Solutions of (2 + 1)- and (3 + 1)-Dimensional Breaking Soliton Equations

Application of Multiple Exp-Function Method to Obtain Multi-Soliton Solutions of (2 + 1)- and (3 + 1)-Dimensional Breaking Soliton Equations Amerc Jourl of Compuol Appled Mhemcs: ; (: 4-47 DOI:.593/j.jcm..8 Applco of Mulple Exp-Fuco Mehod o Ob Mul-Solo Soluos of ( + - (3 + -Dmesol Breg Solo Equos M. T. Drvsh,*, Mlheh Njf, Mohmmd Njf Deprme

More information

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body. The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

Cyclone. Anti-cyclone

Cyclone. Anti-cyclone Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period.

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period. coomcs 435 Meze. Ch Fall 07 Socal Sceces 748 Uversy of Wscos-Madso Sock rces, News ad he ffce Markes Hypohess The rese Value Model Approach o Asse rcg The exbook expresses he sock prce as he prese dscoued

More information

The algebraic immunity of a class of correlation immune H Boolean functions

The algebraic immunity of a class of correlation immune H Boolean functions Ieraoal Coferece o Advaced Elecroc Scece ad Techology (AEST 06) The algebrac mmuy of a class of correlao mmue H Boolea fucos a Jgla Huag ad Zhuo Wag School of Elecrcal Egeerg Norhwes Uversy for Naoales

More information

Continuous Indexed Variable Systems

Continuous Indexed Variable Systems Ieraoal Joural o Compuaoal cece ad Mahemacs. IN 0974-389 Volume 3, Number 4 (20), pp. 40-409 Ieraoal Research Publcao House hp://www.rphouse.com Couous Idexed Varable ysems. Pouhassa ad F. Mohammad ghjeh

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below.

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below. Jorge A. Ramírez HOMEWORK NO. 6 - SOLUTION Problem 1.: Use he Sorage-Idcao Mehod o roue he Ipu hydrograph abulaed below. Tme (h) Ipu Hydrograph (m 3 /s) Tme (h) Ipu Hydrograph (m 3 /s) 0 0 90 450 6 50

More information

Multivariate Regression: A Very Powerful Forecasting Method

Multivariate Regression: A Very Powerful Forecasting Method Archves of Busess Reserch Vol., No. Pulco De: Jue. 5, 8 DOI:.78/r..7. Vslooulos. (8). Mulvre Regresso: A Very Powerful Forecsg Mehod. Archves of Busess Reserch, (), 8. Mulvre Regresso: A Very Powerful

More information

Introduction to mathematical Statistics

Introduction to mathematical Statistics Itroducto to mthemtcl ttstcs Fl oluto. A grou of bbes ll of whom weghed romtely the sme t brth re rdomly dvded to two grous. The bbes smle were fed formul A; those smle were fed formul B. The weght gs

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period.

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period. ublc Affars 974 Meze D. Ch Fall Socal Sceces 748 Uversy of Wscos-Madso Sock rces, News ad he Effce Markes Hypohess (rev d //) The rese Value Model Approach o Asse rcg The exbook expresses he sock prce

More information

Random variables and sampling theory

Random variables and sampling theory Revew Rdom vrbles d smplg theory [Note: Beg your study of ths chpter by redg the Overvew secto below. The red the correspodg chpter the textbook, vew the correspodg sldeshows o the webste, d do the strred

More information

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

Supporting information How to concatenate the local attractors of subnetworks in the HPFP

Supporting information How to concatenate the local attractors of subnetworks in the HPFP n Effcen lgorh for Idenfyng Prry Phenoype rcors of Lrge-Scle Boolen Newor Sng-Mo Choo nd Kwng-Hyun Cho Depren of Mhecs Unversy of Ulsn Ulsn 446 Republc of Kore Depren of Bo nd Brn Engneerng Kore dvnced

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China, Mahemacal ad Compuaoal Applcaos Vol. 5 No. 5 pp. 834-839. Assocao for Scefc Research VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS Hoglag Lu Aguo Xao Yogxag Zhao School of Mahemacs

More information

Solution set Stat 471/Spring 06. Homework 2

Solution set Stat 471/Spring 06. Homework 2 oluo se a 47/prg 06 Homework a Whe he upper ragular elemes are suppressed due o smmer b Le Y Y Y Y A weep o he frs colum o oba: A ˆ b chagg he oao eg ad ec YY weep o he secod colum o oba: Aˆ YY weep o

More information

FORCED VIBRATION of MDOF SYSTEMS

FORCED VIBRATION of MDOF SYSTEMS FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me

More information

Analysis of the Preference Shift of. Customer Brand Selection. and Its Matrix Structure. -Expansion to the second order lag

Analysis of the Preference Shift of. Customer Brand Selection. and Its Matrix Structure. -Expansion to the second order lag Jourl of Compuo & Modellg vol. o. 6-9 ISS: 79-76 (pr) 79-88 (ole) Scepre Ld l of he Preferece Shf of Cuomer Brd Seleco d I Mr Srucure -Epo o he ecod order lg Kuhro Teu rc I ofe oerved h coumer elec he

More information

A New ANFIS Model based on Multi-Input Hamacher T-norm and Subtract Clustering

A New ANFIS Model based on Multi-Input Hamacher T-norm and Subtract Clustering Sed Orders for Reprs o reprs@behmscece.e The Ope Cyberecs & Sysemcs Jourl, 04, 8, 89-834 89 Ope ccess New NFIS Model bsed o Mul-Ipu Hmcher T-orm Subrc Cluserg Feg-Y Zhg Zh-Go Lo * Deprme of Mgeme, Gugx

More information

Review for the Midterm Exam.

Review for the Midterm Exam. Review for he iderm Exm Rememer! Gross re e re Vriles suh s,, /, p / p, r, d R re gross res 2 You should kow he disiio ewee he fesile se d he udge se, d kow how o derive hem The Fesile Se Wihou goverme

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

Chapter 8. Simple Linear Regression

Chapter 8. Simple Linear Regression Chaper 8. Smple Lear Regresso Regresso aalyss: regresso aalyss s a sascal mehodology o esmae he relaoshp of a respose varable o a se of predcor varable. whe here s jus oe predcor varable, we wll use smple

More information

The Properties of Probability of Normal Chain

The Properties of Probability of Normal Chain I. J. Coep. Mah. Sceces Vol. 8 23 o. 9 433-439 HIKARI Ld www.-hkar.co The Properes of Proaly of Noral Cha L Che School of Maheacs ad Sascs Zheghou Noral Uversy Zheghou Cy Hea Provce 4544 Cha cluu6697@sa.co

More information

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR Coquerg gs her es e NTHEM FOR CONGREGTION ND CHOIR I oucg hs hm-hem, whch m be cuded Servce eher s Hm or s hem, he Cogrego m be referred o he No. of he Hm whch he words pper, d ved o o sgg he 1 s, 4 h,

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

Existence Of Solutions For Nonlinear Fractional Differential Equation With Integral Boundary Conditions

Existence Of Solutions For Nonlinear Fractional Differential Equation With Integral Boundary Conditions Reserch Ivey: Ieriol Jourl Of Egieerig Ad Sciece Vol., Issue (April 3), Pp 8- Iss(e): 78-47, Iss(p):39-6483, Www.Reserchivey.Com Exisece Of Soluios For Nolier Frciol Differeil Equio Wih Iegrl Boudry Codiios,

More information

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models Ieraoal Bomerc Coferece 22/8/3, Kobe JAPAN Survval Predco Based o Compoud Covarae uder Co Proporoal Hazard Models PLoS ONE 7. do:.37/oural.poe.47627. hp://d.plos.org/.37/oural.poe.47627 Takesh Emura Graduae

More information

Model for Optimal Management of the Spare Parts Stock at an Irregular Distribution of Spare Parts

Model for Optimal Management of the Spare Parts Stock at an Irregular Distribution of Spare Parts Joural of Evromeal cece ad Egeerg A 7 (08) 8-45 do:0.765/6-598/08.06.00 D DAVID UBLIHING Model for Opmal Maageme of he pare ars ock a a Irregular Dsrbuo of pare ars veozar Madzhov Fores Research Isue,

More information

A MODIFIED CHI-SQUARED GOODNESS-OF-FIT TEST FOR THE KUMARASWAMY GENERALIZED INVERSE WEIBULL DISTRIBUTION AND ITS APPLICATIONS

A MODIFIED CHI-SQUARED GOODNESS-OF-FIT TEST FOR THE KUMARASWAMY GENERALIZED INVERSE WEIBULL DISTRIBUTION AND ITS APPLICATIONS Jourl of Sscs: Advces Theory d Applcos Volume 6 Number 06 Pges 75-305 Avlble hp://scefcdvces.co. DOI: hp://dx.do.org/0.864/js_700749 A MODIFIED CHI-SQUARED GOODNESS-OF-FIT TEST FOR THE KUMARASWAMY GENERALIZED

More information

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices ISSN 746-7659, Egd, UK Jor of Iformo d Compg See Vo. 5, No. 3, 2, pp. 224-232 A Improveme o Ds Sepro of he Shr Compeme d Bods for Deerms of Dgoy Dom Mres Zhohog Hg, Tgzh Hg Shoo of Mhem Sees, Uversy of

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION St Joh s College UPPER V Mthemtcs: Pper Lerg Outcome d ugust 00 Tme: 3 hours Emer: GE Mrks: 50 Modertor: BT / SLS INSTRUCTIONS ND INFORMTION Red the followg structos crefull. Ths questo pper cossts of

More information

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model . Projec Iroduco Fudameals of Speech Recogo Suggesed Projec The Hdde Markov Model For hs projec, s proposed ha you desg ad mpleme a hdde Markov model (HMM) ha opmally maches he behavor of a se of rag sequeces

More information

OPTIMAL BUS DISPATCHING POLICY UNDER VARIABLE DEMAND OVER TIME AND ROUTE LENGTH

OPTIMAL BUS DISPATCHING POLICY UNDER VARIABLE DEMAND OVER TIME AND ROUTE LENGTH OPTIMAL BUS DISPATCHING POLICY UNDE VAIABLE DEMAND OVE TIME AND OUTE LENGTH Prof. Aml S. Kumrge Professor of Cvl Egeerg Uvers of Moruw, Sr L H.A.C. Perer Cvl Egeer Cerl Egeerg Cosulc Bureu, Sr L M.D..P.

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll

More information

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8 emcouc hyscs evces: Bsc rcles, r eo Cher 8 oluos ul rolem oluos Cher 8 rolem oluos 8. he fwr s e ex f The e ex f e e f ex () () f f f f l G e f f ex f 59.9 m 60 m 0 9. m m 8. e ex we c wre hs s e ex h

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

More information

() t ( ) ( ) ( ) ( ) ( ) ( ) ω ω. SURVIVAL Memorize + + x x. m = = =

() t ( ) ( ) ( ) ( ) ( ) ( ) ω ω. SURVIVAL Memorize + + x x. m = = = SURVIVL ' uu λ -Λ : > l + S e e e S ω ο ω ω Ufrm DeMvre S X e Vr X ω λ Eel S X e e λ ω ω ww S + S f ο S + S e where e S S S S S Prcles T X s rm vrble fr remg me ul eh f sus ge f + survvl fuc fr T X f,

More information

Expectation and Moments

Expectation and Moments Her Sr d Joh W. Woods robbl Sscs d Rdom Vrbles or geers 4h ed. erso duco Ic.. ISB: 978----6 Cher 4 eco d omes Secos 4. eced Vlue o Rdom Vrble 5 O he Vld o quo 4.-8 8 4. Codol ecos Codol eco s Rdom Vrble

More information