UNIVERSITY OF NOTTINGHAM

Size: px
Start display at page:

Download "UNIVERSITY OF NOTTINGHAM"

Transcription

1 UNVERSY OF NONGHAM SCHOOL OF ECONOMCS DSCUSSON PAPER NO. 99/7 Surious rjcions by Prron ss in h rsnc of a mislac or scon brak unr h null a-hwan Kim, Shn J. Lybourn, Paul Nwbol School of Economics, Univrsiy of Noingham, Noingham NG7 RD, UK Absrac is known ha Dicky-Fullr ss can la o surious rjcions of h uni roo null hyohsis whn h ru gnraing rocss is iffrnc-saionary wih a brak. Suos now ha an unsuccssful am is ma o allow for a brak, ihr hrough mislac ummy variabls or hrough nglcing a scon brak. is monsra ha surious rjcions can now occur for a broar s of ru brak as han woul b h cas if h ossibiliy of a brak was ignor.

2 . nroucion n a sminal ar, Prron 989 monsra ha Dicky-Fullr ss may hav lil owr whn h ru gnraing rocss is saionary aroun a brokn linar rn s also Monans an Rys 998. Convrsly, Lybourn al 998 show ha whn h ru gnraing rocss is iffrnc saionary, bu wih a brak, rouin alicaion of Dicky-Fullr ss can yil surious rjcions of h uni roo null hyohsis whn h nglc brak is rlaivly arly. his is so for boh a brak in lvl an a brak in rif, alhough hr ar imoran iffrncs bwn h wo cass. Prron 989, 99, 994 an Prron an Voglsang 99, 99 iscuss moificaions of h ss ha circumvn hs ifficulis by incororaing ummy variabls a h brak a. For h rocurs consir hr, h Prron ss hav null isribuions ha ar invarian o h magniu of h brak whn hr is a singl brak a, xognously an corrcly rmin. n his ar, w concnra on h cas of an xognously chosn brak a, bu nrain h ossibiliy ha an incorrc choic is ma. n fac, h Prron s saisics consir ar invarian o any brak in h gnraing rocss a h assum brak a. Our rsuls hrfor aly qually o h ossibly mor racically imoran cas of a gnraing rocss wih wo braks, only on of which is scifically accoun for in h analysis. As in Lybourn al 998, w fin ha a nglc rlaivly arly brak can la o surious rjcions of h uni roo null hyohsis. Morovr, for all bu on of h ss analys, surious rjcions now also aris if a ru brak occurs rlaivly soon afr h assum brak a. hus, for xaml, if h ru gnraing rocss is iffrnc-saionary wih wo rlaivly clos braks, a rjcion of h null hyohsis is likly o occur if ummy variabls accouning for only h arlir of hs braks ar incorora ino h analysis. his hnomnon ariss for boh braks in lvl an braks in rif, hough, as in Lybourn al 998, hr ar imoran iffrncs bwn h wo cass, which w analys rscivly in scions an. W consir boh aiiv oulir an innovaional oulir varians of h Prron saisics, rsricing our horical analysis o h formr. Simulaion vinc suggss only minor iffrncs in rsuls for corrsoning varians of h wo ys of ss.

3 . Braks in lvl Consir h siml iffrnc-saionary gnraing rocss for h sris y y = + ν, ν = ν + ε, =,..., whr ε ar i.i.. isurbancs wih man an sanar viaion σ. A lvl brak of magniu σb, occurring a fracion, hrough h sris, is scifi as / = σb = σk [ > ]. n fac, if b is hl consan as saml siz incrass, h asymoic isribuions of h s saisics ar invarian o brak magniu. Howvr, allowing brak magniu o grow a ra wha is acually foun in mora-siz samls., / gnras limiing isribuional rsuls ha ric h aiiv oulirs varian of h Prron s, wih assum brak fracion, is bas on wo rgrssion ss an whr y = αˆ + βˆ + γˆ + = ρ + + φ ω 4 ω in 4 is an rror rm, an is a ummy variabl allowing a lvl brak a fracion hrough h sris, = [ > ]. 5 Of cours, if a brak is assum a h corrc lac an hr is no aiional brak, so ha =, his is h su analys by Prron 989, 99, 994 an Prron an Voglsang 99. n aricular, h limiing null isribuion of h s saisic, akn hr o b h -raio associa wih h sima of ρ in 4, an no AO lv, is invarian o h brak magniu. Our concrn now is wih h cas whr h assum brak fracion iffrs from h ru fracion. can hn b shown ha, for fix k in, h limiing isribuion of h Prron s saisic is of h form AO E + E + E lv σ + + / / k [ F + F F ] 6 whr is h inicaor funcion = [ ], so ha in h cas =, 6 rucs o / σ F E, which noaion w us for h funcionals in h limiing isribuion givn by Prron 99 an Prron an Voglsang 99. Mor gnrally

4 in xrssion 6, whn hs funcionals n on h assum brak fracion. Also, in 6 E an F ar ranom variabls wih mans, whil h quaniis E an F ar rminisic. n fac, as w s blow, i is hs rminisic quaniis ha omina h bhaviour of h limiing isribuion for moraly larg k, laing o ricions of surious rjcions. Figur shows E an F whn h assum brak fracion is =. 5, σ =, an k =. Algbraic xrssions for hs quaniis ar givn in h Anix. Also, for comarison w show h mans of E + E an F + F. From Figur, i can b sn ha h imac of E is o inuc a vry larg rucion in h man of h numraor in 6 whn h ru brak fracion is ihr vry small or a vry lil mor han h assum brak fracion of.5. Morovr, as can b sn from h grah of F in Figur, i is rcisly for ru braks in hs lacs ha h osiiv quaniy F conribus virually no aiional comnsaing incrmn o h nominaor of 6. W migh hrfor conjcur ha surious rjcions of h uni roo null ar likly o occur boh for vry arly ru braks an for brak fracions a lil highr han. his conjcur is confirm by Figur, which grahs h rsuls of som simulaion xrimns. Sris of = obsrvaions wr gnra from, wih normally isribu innovaions ε an σ =. Brak magnius b of wr s a 5 an. A squnc of ru brak fracions was analys, bu in all xrimns h assum brak fracion was s a.5 in 5, an h s saisic AO lv was calcula from h rgrssions an 4. Nominal 5% significanc lvls wr foun by sing = =. 5. hn, for ohr valus of, Figur shows h rcnags of rjcions of h uni roo null hyohsis a nominal 5%- lvls. Hr an hroughou h ar, simulaions wr bas on, rlicaions. hs rsuls confirm our ricions. Vry frqun rjcions of h null hyohsis occur for boh arly ru braks an for ru braks a lil afr h assum brak a. h firs of hs hnomna is simly h analogu of ha ror by Lybourn al 998 for Dicky-Fullr ss in h rsnc of a nglc brak, whil h scon is an aiional rgion of surious rjcions gnra by h mislac insrion of ummy variabls ino h sima mols. Noic ha h surious rjcion

5 4 hnomnon is almos qually svr in h wo rgions - abou % rjcions for a brak of 5 sanar viaions, an ovr 7% for a brak of sanar viaions. h innovaional oulirs varian of h s is bas on h rgrssion y = + β + γ + φ + ρy α + ω 7 whr ω is an rror rm an is fin in 5. h s saisic O lv is h -raio associa wih h sima of ρ in 7. Using xacly h sam gnraing rocss as for h aiiv oulirs varian of h s, w again sima rjcion rcnags for h O lv s wih s a.5. hs ar also shown in Figur, an ar virually inical o hos of h rgions, hough hr ar sligh iffrncs ousi hs rgions. AO lv s in h mos inrsing is worh r-mhasising ha, whil our rsuls ar bas on h gnraing rocss an, hy woul coninu o hol in h rsnc of an aiional ru brak a im. hy can hus b inrr as h consquncs of allowing for only on brak whn wo ar rsn as wll as of mislacing a singl ru brak.. Braks in rif W now consir h cas whr h ru gnraing rocss is iffrnc-saionary, bu wih a brak in rif. h simls gnraing rocss of his form is y = + ν, ν = ν + ε, =,..., 8 whr ε ar i.i.. isurbancs wih man an sanar viaion σ, an = σb [ > ]. 9 Svral varians of h Prron s migh b mloy whn such a brak is susc. h mos gnral ossibiliy allows for a brak in boh lvl an slo a im h aiiv oulirs varian of h s is hn bas on h wo rgrssion ss, y = αˆ + βˆ + γˆ ˆ + + δ. follow by h rgrssion 4. W consir h s saisic AO r givn by h - raio associa wih h sima of ρ. n, h ummy variabl is fin in 5, an = [ > ].

6 5 nsigh ino h bhaviour of h s saisic whn h assum brak fracion iffrs from h ru fracion can b obain via h robabiliy limi lim. n fac, h -raio ivrgs, bu, as shown in Voglsang an Prron 998, h lim of / AO r ρˆ = [ Var ˆ ρˆ] / os xis. Our inrs hr is o xn hir rsuls o inify h rcis rgion in, sac whr his lim is ngaiv. hrough an aroach skch in h Anix, w fin for h numraor of ha for any nonzro fix brak amoun b of 9, whn, ρˆ whr = [ < ]. hn, sinc h nominaor of is always osiiv, h lim of has h sam sign as h numraor of. hn follows ha h Prron s saisic AO r ivrgs o in h rgion givn by: R = < [ + > < ] hus, h siz of h Prron s ns o % in his rgion for any fix brak amoun b. n aricular hn noic, as for h braks in lvl cas of h rvious scion, hr ar wo ss of valus of h ru brak fracion for which surious rjcions can b xc whn h assum brak fracion. h xrssion for h lim of h nominaor of is consirably mor involv an os n on b, σ 4 an rahr han rovi h algbra w rsn in Figur a a hr-imnsional lo of h lim of / AO r for σ = an b =. For as of inrraion h funcion is runca abov, so ha only valus for h rgion R of 4 ar shown. his is of mos inrs as i is h rgion whr surious rjcions migh b xc for sufficinly larg samls. Byon rvaling h rgion 4, h sha of Figur a is inrsing, as h h of h lim shoul giv an inicaion of h likly rlaiv svriy of h surious rjcion hnomnon. Firs, noic ha h funcion falls an hn vnually riss boh as incrass from an as incrass from. his suggss ha h mos svr cass of surious rjcions ar likly o occur whn is a lil grar han, an again whn is a lil grar han. his is in conras o h rsuls of h rvious scion, whr w foun, for xaml, a "wors cas" occurs whn h ru brak is immialy afr

7 6 h assum brak. Scon, which of h wo isjoin ss of valus conains h svrs cas of surious rjcions woul sm o n on h locaion of in aricular on whhr h assum brak fracion is mor or lss han on-half., an hs ricions ar closly vrifi by h simulaion rsuls rsn in Figur 4, bas on sris of = obsrvaions gnra from 8, 9 wih ε normally isribu wih σ =, an valus of.5 an. for b. Prcnags of rjcions of h uni roo null hyohsis for nominal 5%-lvl vrsions for h AO s ar shown. n ar a of h figur, h assum brak fracion is =. 5. r wo rgions of srious surious rjcions ar rval - on whr h ru brak occurs qui arly in h sris, an h scon whr h ru brak is soon afr h assum brak. h osiion is virually inical in hs wo rgions, h mos svr cass occurring a roorion. from h bginning of h sris an h sam amoun from h assum brak. n ar b of Figur 4, h assum brak fracion is =.85. n ha cas, h iniial rgion of surious rjcions is broar an mor svr, whil h scon rgion is narrowr an lss svr han in h =. 5 cas. h innovaional oulirs varian of h s is bas on h rgrssion y = + β + γ + φ + δ + ρy α + ω 5 whr ω is an rror rm. Figur 4 also shows simulaion vinc on h s saisic O, h -raio associa wih h sima of ρ from 5. h r icur is broaly similar o ha for h aiiv oulirs varian of h s, hough i aars ha h surious rjcion hnomnon is a lil mor svr an xns o a somwha broar rang of valus of h ru brak fracion for h innovaion oulirs s. h ss iscuss so far in his scion rmi braks in boh lvl an slo. An aiiv oulirs s incororaing jus h lar is bas on h wo rgrssion ss an y = αˆ + βˆ + δˆ + 6 = ρ + ω 7 W hn consir h s saisic AO r, h -raio associa wih h sima of ρ from 7. As no for xaml in foono 4 of Prron 994, h

8 7 corrsoning innovaional oulir varian of his s is usually no rcommn as h asymoic null isribuion of h s saisic is no invarian o h magniu of any corrcly scifi brak unr h null hyohsis. W invsiga h lim of / AO r, again for h gnraing rocss 8, 9. Wriing h quaniy of inrs in h sam form as h righ-han si of, i can b shown ha, for, + [ + + ] ρ ˆ. 8 [ ] h funcion 8, an hrfor h lim of / AO r, is ngaiv in h rgion R = { < [ < + ]} { > [ < ]}. 9 follows ha h s saisic AO r ivrgs o in h rgion 9, so ha for fix brak magnius b, surious rjcions can b xc in his rgion for sufficinly larg saml sizs. h algbraic xrssion for h lim of / AO r is xrmly lnghy. h funcion, runca abov, is grah for σ = an b = in Figur b. h conras wih Figur a is qui sriking, suggsing ha h surious rjcion hnomnon will sm qui iffrn in h wo cass. n aricular, noic ha h rgion associa wih > - ha is, h scon lmn in 9 - is boh qui small an shallow, xning only ovr rlaivly low valus of. ha suggss ha, unlss h ru an mislac braks ar qui arly, a scon rgion of surious rjcions will no b foun. n, vn in hs cass, surious rjcions will occur on ihr si of h assum brak a an b rsric o qui low valus of. Figur b also suggss ha, h grar is, h broar will b h inrval in which surious rjcions ar foun, an h mor svr will b hs rjcions. Noic ha, as aroachs, R of 9 ns o <, whil as aroachs, R ns o <. h corrsoning rgion for surious rjcions by Dicky- Fullr ss in h rsnc of a brak unr h null is shown by Lybourn al, 998, o b <.. hus, whil h insrion an locaion of a mislac brak in h AO r s can b xc o hav som imac on h surious rjcion hnomnon, ha imac shoul b far lss ramaic han for h AO r s.

9 8 Figur 5 shows simulaion rsuls for h alicaion of h h sam gnraing mols as for h AO r s, using AO r s in Figur 4. Again, as in Figur 4, assum brak fracions of =. 5 an.85 wr us. As ric, only on rgion of surious rjcions is foun in hs cass - ha rgion incrasing in wih, an ning in svriy as incrass. Noic also ha h surious rjcion hnomnon is a lil mor svr for h AO r s han for h AO r s of Figur 4, in h sns ha h rjcion frquncy is somwha highr in h wors cass for h formr han for h lar. 4. Summary W hav shown horically an by simulaion ha Prron ss bas on a mislac srucural brak can gnra wo rgions of surious rjcions of h uni roo null hyohsis. h firs of hs is whr h ru brak in h sris is rlaivly arly, mirroring h finings of Lybourn al 998 of surious rjcions from Dicky- Fullr ss in h rsnc of a brak unr h null. Howvr, surious rjcions now also occur if h ru brak in h sris is rlaivly soon afr h assum brak. his hnomnon can b qually svr in h scon rgion as in h firs. f a im sris has a srucural brak, hn i is nirly ossibl, if h assum brak is a lil arlir han h ru brak, for surious rjcions of h uni roo null hyohsis o occur hrough alicaion of h Prron s in cass whr his hnomnon woul no b foun hrough rouin alicaion of h Dicky-Fullr s, ignoring h ossibiliy of a brak. h rsuls can also b inrr as a monsraion of h onial for surious rjcions of h uni roo null whn scific allowanc in h analysis is ma for only h firs of wo braks clos in im. Of cours, hs rsuls shoul no b inrr as suggsing ha uni roo ss, such as h Prron ss, ha allow for h ossibiliy of srucural braks ar of limi valu. On h conrary, our rsuls oin in h ohr ircion, inicaing h snsiiviy of h s oucoms o scificaion of boh h numbr an locaion of any braks. is qui clar ha any rminaion of h issu of uni auorgrssiv roos is inimaly link wih succssful rsoluion of hs issus concrning braks. Finally, w also no ha our finings also xn o ss such as ha of Zivo an Anrws 99 which nognis h brak oin, an ar bas on h mos ngaiv valu of h Prron-y uni roo s across all ossibl valus for. h

10 9 criical valus of hs ss ar calcula assuming no brak unr h null. Howvr, whn a brak xiss, our rsuls suggs ha h acual criical valus will b much mor ngaiv han whn no brak xiss. hus, surious rjcions of h uni roo null will aris if h convnional criical valus for such ss ar mloy. Rfrncs Monans, A., Rys, M., 998, Effc of a shif in h rn funcion on Dicky-Fullr uni roo ss. Economric hory 4, Lybourn, S.J., Mills,.C., Nwbol, P., 998, Surious rjcions by Dicky Fullr ss in h rsnc of a brak unr h null. Journal of Economrics 87, 9-. Prron, P., 989, h Gra Crash, h oil ric shock an h uni roo hyohsis. Economrica 57, 6-4. Prron, P., 99, h Gra Crash, h oil ric shock an h uni roo hyohsis: Erraum. Economrica 6, Prron, P., 994, rn, uni roo an srucural chang in macroconomic im sris. n B.B. Rao,., Coingraion for h Ali Economis, Macmillan, -46. Prron, P. an.j. Voglsang, 99, Nonsaionariy an lvl shifs wih an alicaion o urchasing owr ariy. Journal of Businss an Economic Saisics, -. Prron, P. an Voglsang,.J., 99, A no on h asymoic isribuions of uni roo ss in h aiiv oulir mol wih braks. Rvisa Economria, 8-. Voglsang,.J. an Prron, P., 998, Aiional ss for a uni roo allowing for a brak in h rn funcion a an unknown im. nrnaional Economic Rviw, 9, 7-. Zivo, E. an Anrws, D.W.K., 99, Furhr vinc on h Gra Crash, h oil ric shock an h uni roo hyohsis. Journal of Businss an Economic Saisics, 5-7.

11 Anix Braks in lvl A horical ricion of surious rjcions foun for h aiiv oulirs varian of h Prron s is bas on h following rsuls, which w sa wihou roof: Consir h gnraing rocss, wih k fix. hn h s saisic AO lv, h -raio associa wih h las squars sima of ρ in 4, has h limiing null isribuion givn by 6. n ha xrssion, E an F, hr akn o b funcions of, ar h ranom variabls givn in h corrsoning rsul of Prron 99 an Prron an Voglsang 99 for h cas =. Also, E an F ar ranom variabls funcions of h Winr rocss in C [,] wih mans. h fix numbrs E an F ar givn by an whr E σ k + σ k / H / D + σ k H / D F + D σ k + H / + σ + k H / D σ k H / D σ k + H / D + σ k HH / D D / σ k [ H / σ k ] A. A. H / σ k + [ + h funcions E an F givn by A. an A. ar grah in Figur for k =, σ = an assum brak fracion =.5. is h bhaviour of hs funcions for mora k ha suggss h ossibiliy of surious rjcions whn h Prron s is ali wih a mislac brak. ]. Braks in rif W skch how o obain h lim givn by. Consir h firs rgrssion s. h Frisch-Waugh-Lovll horm givs us θˆ = A b + b

12 whr δ γ β θ ˆ ˆ ˆ ˆ, A, b, v v v b, i i, i i, an all variabls ar xrss as viaions from hir saml mans. can b shown ha A AD D, b b D, b D whr D, D, A is a non-singular marix, b is a vcor. hrfor, ˆ b A D θ. n orr o obain h lim for ach comonn in θˆ, firs riv all lims in A an b, an hn us h Symbolic Mah oolbox in MALAB o comu b A symbolically. hn w hav h following rsuls: / ˆ + β A. / ˆ γ / ˆ δ. From h scon s, on can comu ha F E / ˆ = ρ whr + ] [ ] [ E an ] [ F. Wih sraighforwar bu ious algbra, on can show using h rsuls in A. ha / E + / F + which livrs h sir rsul in.

Double Slits in Space and Time

Double Slits in Space and Time Doubl Slis in Sac an Tim Gorg Jons As has bn ror rcnly in h mia, a am l by Grhar Paulus has monsra an inrsing chniqu for ionizing argon aoms by using ulra-shor lasr ulss. Each lasr uls is ffcivly on an

More information

Midterm exam 2, April 7, 2009 (solutions)

Midterm exam 2, April 7, 2009 (solutions) Univrsiy of Pnnsylvania Dparmn of Mahmaics Mah 26 Honors Calculus II Spring Smsr 29 Prof Grassi, TA Ashr Aul Midrm xam 2, April 7, 29 (soluions) 1 Wri a basis for h spac of pairs (u, v) of smooh funcions

More information

Chapter 2 The Derivative Business Calculus 99

Chapter 2 The Derivative Business Calculus 99 Chapr Th Drivaiv Businss Calculus 99 Scion 5: Drivaivs of Formulas In his scion, w ll g h rivaiv ruls ha will l us fin formulas for rivaivs whn our funcion coms o us as a formula. This is a vry algbraic

More information

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o

More information

Ratio-Product Type Exponential Estimator For Estimating Finite Population Mean Using Information On Auxiliary Attribute

Ratio-Product Type Exponential Estimator For Estimating Finite Population Mean Using Information On Auxiliary Attribute Raio-Produc T Exonnial Esimaor For Esimaing Fini Poulaion Man Using Informaion On Auxiliar Aribu Rajsh Singh, Pankaj hauhan, and Nirmala Sawan, School of Saisics, DAVV, Indor (M.P., India (rsinghsa@ahoo.com

More information

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control MEM 355 Prformanc Enhancmn of Dynamical Sysms A Firs Conrol Problm - Cruis Conrol Harry G. Kwany Darmn of Mchanical Enginring & Mchanics Drxl Univrsiy Cruis Conrol ( ) mv = F mg sinθ cv v +.2v= u 9.8θ

More information

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b 4. Th Uniform Disribuion Df n: A c.r.v. has a coninuous uniform disribuion on [a, b] whn is pdf is f x a x b b a Also, b + a b a µ E and V Ex4. Suppos, h lvl of unblivabiliy a any poin in a Transformrs

More information

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018 DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS Aoc. Prof. Dr. Burak Kllci Spring 08 OUTLINE Th Laplac Tranform Rgion of convrgnc for Laplac ranform Invr Laplac ranform Gomric valuaion

More information

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano Expcaions: Th Basic Prpard by: Frnando Quijano and Yvonn Quijano CHAPTER CHAPTER14 2006 Prnic Hall Businss Publishing Macroconomics, 4/ Olivir Blanchard 14-1 Today s Lcur Chapr 14:Expcaions: Th Basic Th

More information

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 )

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 ) AR() Procss Th firs-ordr auorgrssiv procss, AR() is whr is WN(0, σ ) Condiional Man and Varianc of AR() Condiional man: Condiional varianc: ) ( ) ( Ω Ω E E ) var( ) ) ( var( ) var( σ Ω Ω Ω Ω E Auocovarianc

More information

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form:

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form: Th Ingraing Facor Mhod In h prvious xampls of simpl firs ordr ODEs, w found h soluions by algbraically spara h dpndn variabl- and h indpndn variabl- rms, and wri h wo sids of a givn quaion as drivaivs,

More information

2. The Laplace Transform

2. The Laplace Transform Th aac Tranorm Inroucion Th aac ranorm i a unamna an vry uu oo or uying many nginring robm To in h aac ranorm w conir a comx variab σ, whr σ i h ra ar an i h imaginary ar or ix vau o σ an w viw a a oin

More information

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to:

1. Inverse Matrix 4[(3 7) (02)] 1[(0 7) (3 2)] Recall that the inverse of A is equal to: Rfrncs Brnank, B. and I. Mihov (1998). Masuring monary policy, Quarrly Journal of Economics CXIII, 315-34. Blanchard, O. R. Proi (00). An mpirical characrizaion of h dynamic ffcs of changs in govrnmn spnding

More information

Charging of capacitor through inductor and resistor

Charging of capacitor through inductor and resistor cur 4&: R circui harging of capacior hrough inducor and rsisor us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R, an inducor of inducanc and a y K in sris.

More information

Copyright 2012 Pearson Education, Inc. Publishing as Prentice Hall.

Copyright 2012 Pearson Education, Inc. Publishing as Prentice Hall. Chapr Rviw 0 6. ( a a ln a. This will qual a if an onl if ln a, or a. + k an (ln + c. Thrfor, a an valu of, whr h wo curvs inrsc, h wo angn lins will b prpnicular. 6. (a Sinc h lin passs hrough h origin

More information

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees CPSC 211 Daa Srucurs & Implmnaions (c) Txas A&M Univrsiy [ 259] B-Trs Th AVL r and rd-black r allowd som variaion in h lnghs of h diffrn roo-o-laf pahs. An alrnaiv ida is o mak sur ha all roo-o-laf pahs

More information

The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function

The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function. The Transfer Function A gnraliation of th frquncy rsons function Th convolution sum scrition of an LTI iscrt-tim systm with an imuls rsons h[n] is givn by h y [ n] [ ] x[ n ] Taing th -transforms of both sis w gt n n h n n

More information

Lecture 6 - Testing Restrictions on the Disturbance Process (References Sections 2.7 and 2.10, Hayashi)

Lecture 6 - Testing Restrictions on the Disturbance Process (References Sections 2.7 and 2.10, Hayashi) Lecure 6 - esing Resricions on he Disurbance Process (References Secions 2.7 an 2.0, Hayashi) We have eveloe sufficien coniions for he consisency an asymoic normaliy of he OLS esimaor ha allow for coniionally

More information

Institute of Actuaries of India

Institute of Actuaries of India Insiu of Acuaris of India ubjc CT3 Probabiliy and Mahmaical aisics Novmbr Examinaions INDICATIVE OLUTION Pag of IAI CT3 Novmbr ol. a sampl man = 35 sampl sandard dviaion = 36.6 b for = uppr bound = 35+*36.6

More information

Final Exam : Solutions

Final Exam : Solutions Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b

More information

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors Boc/DiPrima 9 h d, Ch.: Linar Equaions; Mhod of Ingraing Facors Elmnar Diffrnial Equaions and Boundar Valu Problms, 9 h diion, b William E. Boc and Richard C. DiPrima, 009 b John Wil & Sons, Inc. A linar

More information

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems Inrucor Soluion for Aignmn Chapr : Tim Domain Anali of LTIC Sm Problm i a 8 x x wih x u,, an Zro-inpu rpon of h m: Th characriic quaion of h LTIC m i i 8, which ha roo a ± j Th zro-inpu rpon i givn b zi

More information

Chapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System

Chapter 5 The Laplace Transform. x(t) input y(t) output Dynamic System EE 422G No: Chapr 5 Inrucor: Chung Chapr 5 Th Laplac Tranform 5- Inroducion () Sym analyi inpu oupu Dynamic Sym Linar Dynamic ym: A procor which proc h inpu ignal o produc h oupu dy ( n) ( n dy ( n) +

More information

CSE 245: Computer Aided Circuit Simulation and Verification

CSE 245: Computer Aided Circuit Simulation and Verification CSE 45: Compur Aidd Circui Simulaion and Vrificaion Fall 4, Sp 8 Lcur : Dynamic Linar Sysm Oulin Tim Domain Analysis Sa Equaions RLC Nwork Analysis by Taylor Expansion Impuls Rspons in im domain Frquncy

More information

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison Economics 302 (Sc. 001) Inrmdia Macroconomic Thory and Policy (Spring 2011) 3/28/2012 Insrucor: Prof. Mnzi Chinn Insrucor: Prof. Mnzi Chinn UW Madison 16 1 Consumpion Th Vry Forsighd dconsumr A vry forsighd

More information

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -

More information

Microscopic Flow Characteristics Time Headway - Distribution

Microscopic Flow Characteristics Time Headway - Distribution CE57: Traffic Flow Thory Spring 20 Wk 2 Modling Hadway Disribuion Microscopic Flow Characrisics Tim Hadway - Disribuion Tim Hadway Dfiniion Tim Hadway vrsus Gap Ahmd Abdl-Rahim Civil Enginring Dparmn,

More information

Probabilistic Graphical Models

Probabilistic Graphical Models School o Cour Scinc robabilisic Grahical Mols Aroia Inrnc: Mon Carlo hos Eric ing Lcur 6 March 7 204 Raing: S class wbsi Eric ing @ CMU 2005-204 Aroachs o inrnc Eac inrnc algorihs Th liinaion algorih Mssag-assing

More information

Ma/CS 6a Class 15: Flows and Bipartite Graphs

Ma/CS 6a Class 15: Flows and Bipartite Graphs //206 Ma/CS 6a Cla : Flow and Bipari Graph By Adam Shffr Rmindr: Flow Nwork A flow nwork i a digraph G = V, E, oghr wih a ourc vrx V, a ink vrx V, and a capaciy funcion c: E N. Capaciy Sourc 7 a b c d

More information

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2 Mah 0 Homwork S 6 Soluions 0 oins. ( ps) I ll lav i o you o vrify ha y os sin = +. Th guss for h pariular soluion and is drivaivs is blow. Noi ha w ndd o add s ono h las wo rms sin hos ar xaly h omplimnary

More information

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016

Applied Statistics and Probability for Engineers, 6 th edition October 17, 2016 Applid Saisics and robabiliy for Enginrs, 6 h diion Ocobr 7, 6 CHATER Scion - -. a d. 679.. b. d. 88 c d d d. 987 d. 98 f d.. Thn, = ln. =. g d.. Thn, = ln.9 =.. -7. a., by symmry. b.. d...6. 7.. c...

More information

Relation between Fourier Series and Transform

Relation between Fourier Series and Transform EE 37-3 8 Ch. II: Inro. o Sinls Lcur 5 Dr. Wih Abu-Al-Su Rlion bwn ourir Sris n Trnsform Th ourir Trnsform T is riv from h finiion of h ourir Sris S. Consir, for xmpl, h prioic complx sinl To wih prio

More information

Chapter 3 Common Families of Distributions

Chapter 3 Common Families of Distributions Chaer 3 Common Families of Disribuions Secion 31 - Inroducion Purose of his Chaer: Caalog many of common saisical disribuions (families of disribuions ha are indeed by one or more arameers) Wha we should

More information

Chapter 12 Introduction To The Laplace Transform

Chapter 12 Introduction To The Laplace Transform Chapr Inroducion To Th aplac Tranorm Diniion o h aplac Tranorm - Th Sp & Impul uncion aplac Tranorm o pciic uncion 5 Opraional Tranorm Applying h aplac Tranorm 7 Invr Tranorm o Raional uncion 8 Pol and

More information

First Lecture of Machine Learning. Hung-yi Lee

First Lecture of Machine Learning. Hung-yi Lee Firs Lcur of Machin Larning Hung-yi L Larning o say ys/no Binary Classificaion Larning o say ys/no Sam filring Is an -mail sam or no? Rcommndaion sysms rcommnd h roduc o h cusomr or no? Malwar dcion Is

More information

XV Exponential and Logarithmic Functions

XV Exponential and Logarithmic Functions MATHEMATICS 0-0-RE Dirnial Calculus Marin Huard Winr 08 XV Eponnial and Logarihmic Funcions. Skch h graph o h givn uncions and sa h domain and rang. d) ) ) log. Whn Sarah was born, hr parns placd $000

More information

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT [Typ x] [Typ x] [Typ x] ISSN : 974-7435 Volum 1 Issu 24 BioTchnology 214 An Indian Journal FULL PAPE BTAIJ, 1(24), 214 [15197-1521] A sag-srucurd modl of a singl-spcis wih dnsiy-dpndn and birh pulss LI

More information

whereby we can express the phase by any one of the formulas cos ( 3 whereby we can express the phase by any one of the formulas

whereby we can express the phase by any one of the formulas cos ( 3 whereby we can express the phase by any one of the formulas Third In-Class Exam Soluions Mah 6, Profssor David Lvrmor Tusday, 5 April 07 [0] Th vrical displacmn of an unforcd mass on a spring is givn by h 5 3 cos 3 sin a [] Is his sysm undampd, undr dampd, criically

More information

Why Laplace transforms?

Why Laplace transforms? MAE4 Linar ircui Why Lalac ranform? Firordr R cc v v v KVL S R inananou for ach Subiu lmn rlaion v S Ordinary diffrnial quaion in rm of caacior volag Lalac ranform Solv Invr LT V u, v Ri, i A R V A _ v

More information

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER A THREE COPARTENT ATHEATICAL ODEL OF LIVER V. An N. Ch. Paabhi Ramacharyulu Faculy of ahmaics, R D collgs, Hanamonda, Warangal, India Dparmn of ahmaics, Naional Insiu of Tchnology, Warangal, India E-ail:

More information

Midterm Examination (100 pts)

Midterm Examination (100 pts) Econ 509 Spring 2012 S.L. Parn Midrm Examinaion (100 ps) Par I. 30 poins 1. Dfin h Law of Diminishing Rurns (5 ps.) Incrasing on inpu, call i inpu x, holding all ohr inpus fixd, on vnuall runs ino h siuaion

More information

OPTIMAL DIVIDENDS AND CAPITAL INJECTIONS IN THE DUAL MODEL WITH DIFFUSION ABSTRACT KEYWORDS

OPTIMAL DIVIDENDS AND CAPITAL INJECTIONS IN THE DUAL MODEL WITH DIFFUSION ABSTRACT KEYWORDS OPTIMAL DIVIDENDS AND CAPITAL INJECTIONS IN THE DUAL MODEL WITH DIFFUSION BY BENJAMIN AVANZI, JONATHAN SHEN, BERNARD WONG ABSTRACT Th ual mol wih iffusion is aroria for comanis wih coninuous xnss ha ar

More information

H is equal to the surface current J S

H is equal to the surface current J S Chapr 6 Rflcion and Transmission of Wavs 6.1 Boundary Condiions A h boundary of wo diffrn mdium, lcromagnic fild hav o saisfy physical condiion, which is drmind by Maxwll s quaion. This is h boundary condiion

More information

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline.

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline. Dlin Curvs Dlin Curvs ha lo flow ra vs. im ar h mos ommon ools for forasing roduion and monioring wll rforman in h fild. Ths urvs uikly show by grahi mans whih wlls or filds ar roduing as xd or undr roduing.

More information

B) 25y e. 5. Find the second partial f. 6. Find the second partials (including the mixed partials) of

B) 25y e. 5. Find the second partial f. 6. Find the second partials (including the mixed partials) of Sampl Final 00 1. Suppos z = (, y), ( a, b ) = 0, y ( a, b ) = 0, ( a, b ) = 1, ( a, b ) = 1, and y ( a, b ) =. Thn (a, b) is h s is inconclusiv a saddl poin a rlaiv minimum a rlaiv maimum. * (Classiy

More information

Wave Equation (2 Week)

Wave Equation (2 Week) Rfrnc Wav quaion ( Wk 6.5 Tim-armonic filds 7. Ovrviw 7. Plan Wavs in Losslss Mdia 7.3 Plan Wavs in Loss Mdia 7.5 Flow of lcromagnic Powr and h Poning Vcor 7.6 Normal Incidnc of Plan Wavs a Plan Boundaris

More information

Laplace Transforms recap for ccts

Laplace Transforms recap for ccts Lalac Tranform rca for cc Wha h big ida?. Loo a iniial condiion ron of cc du o caacior volag and inducor currn a im Mh or nodal analyi wih -domain imdanc rianc or admianc conducanc Soluion of ODE drivn

More information

Abstract. 1 Introduction

Abstract. 1 Introduction A ToA-bas Aroach o NLOS Localizaion Using Low-Frquncy Soun Lin Chi Mak an Tomonari Furukawa ARC Cnr of Excllnc for Auonomous Sysms School of Mchanical an Manufacuring Enginring Th Univrsiy of Nw Souh Wals

More information

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system:

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system: Undrdamd Sysms Undrdamd Sysms nd Ordr Sysms Ouu modld wih a nd ordr ODE: d y dy a a1 a0 y b f If a 0 0, hn: whr: a d y a1 dy b d y dy y f y f a a a 0 0 0 is h naural riod of oscillaion. is h daming facor.

More information

( ) ( ) + = ( ) + ( )

( ) ( ) + = ( ) + ( ) Mah 0 Homwork S 6 Soluions 0 oins. ( ps I ll lav i o you vrify ha h omplimnary soluion is : y ( os( sin ( Th guss for h pariular soluion and is drivaivs ar, +. ( os( sin ( ( os( ( sin ( Y ( D 6B os( +

More information

EXERCISE - 01 CHECK YOUR GRASP

EXERCISE - 01 CHECK YOUR GRASP DIFFERENTIAL EQUATION EXERCISE - CHECK YOUR GRASP 7. m hn D() m m, D () m m. hn givn D () m m D D D + m m m m m m + m m m m + ( m ) (m ) (m ) (m + ) m,, Hnc numbr of valus of mn will b. n ( ) + c sinc

More information

Voltage v(z) ~ E(z)D. We can actually get to this wave behavior by using circuit theory, w/o going into details of the EM fields!

Voltage v(z) ~ E(z)D. We can actually get to this wave behavior by using circuit theory, w/o going into details of the EM fields! Considr a pair of wirs idal wirs ngh >, say, infinily long olag along a cabl can vary! D olag v( E(D W can acually g o his wav bhavior by using circui hory, w/o going ino dails of h EM filds! Thr

More information

5. An object moving along an x-coordinate axis with its scale measured in meters has a velocity of 6t

5. An object moving along an x-coordinate axis with its scale measured in meters has a velocity of 6t AP CALCULUS FINAL UNIT WORKSHEETS ACCELERATION, VELOCTIY AND POSITION In problms -, drmin h posiion funcion, (), from h givn informaion.. v (), () = 5. v ()5, () = b g. a (), v() =, () = -. a (), v() =

More information

FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Introduction and Linear Systems

FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Introduction and Linear Systems FIRST-ORDER SYSTEMS OF ORDINARY DIFFERENTIAL EQUATIONS I: Inroducion and Linar Sysms David Lvrmor Dparmn of Mahmaics Univrsiy of Maryland 9 Dcmbr 0 Bcaus h prsnaion of his marial in lcur will diffr from

More information

Control System Engineering (EE301T) Assignment: 2

Control System Engineering (EE301T) Assignment: 2 Conrol Sysm Enginring (EE0T) Assignmn: PART-A (Tim Domain Analysis: Transin Rspons Analysis). Oain h rspons of a uniy fdack sysm whos opn-loop ransfr funcion is (s) s ( s 4) for a uni sp inpu and also

More information

Elementary Differential Equations and Boundary Value Problems

Elementary Differential Equations and Boundary Value Problems Elmnar Diffrnial Equaions and Boundar Valu Problms Boc. & DiPrima 9 h Ediion Chapr : Firs Ordr Diffrnial Equaions 00600 คณ ตศาสตร ว ศวกรรม สาขาว ชาว ศวกรรมคอมพ วเตอร ป การศ กษา /55 ผศ.ดร.อร ญญา ผศ.ดร.สมศ

More information

The Variance-Covariance Matrix

The Variance-Covariance Matrix Th Varanc-Covaranc Marx Our bggs a so-ar has bn ng a lnar uncon o a s o daa by mnmzng h las squars drncs rom h o h daa wh mnsarch. Whn analyzng non-lnar daa you hav o us a program l Malab as many yps o

More information

MARK SCHEME for the October/November 2014 series 9231 MATHEMATICS. 9231/12 Paper 1, maximum raw mark 100

MARK SCHEME for the October/November 2014 series 9231 MATHEMATICS. 9231/12 Paper 1, maximum raw mark 100 CAMBRIDGE INTERNATIONAL EXAMINATIONS Cambrig Inrnaional Aanc Ll MARK SCHEME for h Ocobr/Nombr sris 9 MATHEMATICS 9/ Papr, maimum raw mar This mar schm is publish as an ai o achrs an canias, o inica h rquirmns

More information

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review Spring 6 Procss Dynamics, Opraions, and Conrol.45 Lsson : Mahmaics Rviw. conx and dircion Imagin a sysm ha varis in im; w migh plo is oupu vs. im. A plo migh imply an quaion, and h quaion is usually an

More information

Transfer function and the Laplace transformation

Transfer function and the Laplace transformation Lab No PH-35 Porland Sa Univriy A. La Roa Tranfr funcion and h Laplac ranformaion. INTRODUTION. THE LAPLAE TRANSFORMATION L 3. TRANSFER FUNTIONS 4. ELETRIAL SYSTEMS Analyi of h hr baic paiv lmn R, and

More information

PhysicsAndMathsTutor.com

PhysicsAndMathsTutor.com C3 Eponnials and logarihms - Eponnial quaions. Rabbis wr inroducd ono an island. Th numbr of rabbis, P, yars afr hy wr inroducd is modlld by h quaion P = 3 0, 0 (a) Wri down h numbr of rabbis ha wr inroducd

More information

Themes. Flexible exchange rates with inflation targeting. Expectations formation under flexible exchange rates

Themes. Flexible exchange rates with inflation targeting. Expectations formation under flexible exchange rates CHAPTER 25 THE OPEN ECONOMY WITH FLEXIBLE EXCHANGE RATES Thms Flxibl xchang ras wih inlaion arging Expcaions ormaion undr lxibl xchang ras Th AS-AD modl wih lxibl xchang ras Macroconomic adjusmn undr lxibl

More information

Multiple Short Term Infusion Homework # 5 PHA 5127

Multiple Short Term Infusion Homework # 5 PHA 5127 Multipl Short rm Infusion Homwork # 5 PHA 527 A rug is aministr as a short trm infusion. h avrag pharmacokintic paramtrs for this rug ar: k 0.40 hr - V 28 L his rug follows a on-compartmnt boy mol. A 300

More information

Lecture 4: Laplace Transforms

Lecture 4: Laplace Transforms Lur 4: Lapla Transforms Lapla and rlad ransformaions an b usd o solv diffrnial quaion and o rdu priodi nois in signals and imags. Basially, hy onvr h drivaiv opraions ino mulipliaion, diffrnial quaions

More information

On the Speed of Heat Wave. Mihály Makai

On the Speed of Heat Wave. Mihály Makai On h Spd of Ha Wa Mihály Maai maai@ra.bm.hu Conns Formulaion of h problm: infini spd? Local hrmal qulibrium (LTE hypohsis Balanc quaion Phnomnological balanc Spd of ha wa Applicaion in plasma ranspor 1.

More information

I) Title: Rational Expectations and Adaptive Learning. II) Contents: Introduction to Adaptive Learning

I) Title: Rational Expectations and Adaptive Learning. II) Contents: Introduction to Adaptive Learning I) Til: Raional Expcaions and Adapiv Larning II) Conns: Inroducion o Adapiv Larning III) Documnaion: - Basdvan, Olivir. (2003). Larning procss and raional xpcaions: an analysis using a small macroconomic

More information

PS#4 due today (in class or before 3pm, Rm ) cannot ignore the spatial dimensions

PS#4 due today (in class or before 3pm, Rm ) cannot ignore the spatial dimensions Topic I: Sysms Cll Biology Spaial oscillaion in. coli PS# u oay in class or bfor pm Rm. 68-7 similar o gnic oscillaors s bu now w canno ignor h spaial imnsions biological funcion: rmin h cnr of h cll o

More information

The transition:transversion rate ratio vs. the T-ratio.

The transition:transversion rate ratio vs. the T-ratio. PhyloMah Lcur 8 by Dan Vandrpool March, 00 opics of Discussion ransiion:ransvrsion ra raio Kappa vs. ransiion:ransvrsion raio raio alculaing h xpcd numbr of subsiuions using marix algbra Why h nral im

More information

= x. I (x,y ) Example: Translation. Operations depend on pixel s Coordinates. Context free. Independent of pixel values. I(x,y) Forward mapping:

= x. I (x,y ) Example: Translation. Operations depend on pixel s Coordinates. Context free. Independent of pixel values. I(x,y) Forward mapping: Gomric Transormaion Oraions dnd on il s Coordinas. Con r. Indndn o il valus. (, ) ' (, ) ' I (, ) I ' ( (, ), ( ) ), (,) (, ) I(,) I (, ) Eaml: Translaion (, ) (, ) (, ) I(, ) I ' Forward Maing Forward

More information

SOLUTIONS. 1. Consider two continuous random variables X and Y with joint p.d.f. f ( x, y ) = = = 15. Stepanov Dalpiaz

SOLUTIONS. 1. Consider two continuous random variables X and Y with joint p.d.f. f ( x, y ) = = = 15. Stepanov Dalpiaz STAT UIUC Pracic Problms #7 SOLUTIONS Spanov Dalpiaz Th following ar a numbr of pracic problms ha ma b hlpful for compling h homwor, and will lil b vr usful for suding for ams.. Considr wo coninuous random

More information

Lecture 2: Bayesian inference - Discrete probability models

Lecture 2: Bayesian inference - Discrete probability models cu : Baysian infnc - Disc obabiliy modls Many hings abou Baysian infnc fo disc obabiliy modls a simila o fqunis infnc Disc obabiliy modls: Binomial samling Samling a fix numb of ials fom a Bnoulli ocss

More information

How to Deal with Structural Breaks in Practical Cointegration Analysis

How to Deal with Structural Breaks in Practical Cointegration Analysis How o Deal wih Srucural Breaks in Pracical Coinegraion Analysis Roselyne Joyeux * School of Economic and Financial Sudies Macquarie Universiy December 00 ABSTRACT In his noe we consider he reamen of srucural

More information

Physics 160 Lecture 3. R. Johnson April 6, 2015

Physics 160 Lecture 3. R. Johnson April 6, 2015 Physics 6 Lcur 3 R. Johnson April 6, 5 RC Circui (Low-Pass Filr This is h sam RC circui w lookd a arlir h im doma, bu hr w ar rsd h frquncy rspons. So w pu a s wav sad of a sp funcion. whr R C RC Complx

More information

Sales Tax: Specific or Ad Valorem Tax for a Non-renewable Resource?

Sales Tax: Specific or Ad Valorem Tax for a Non-renewable Resource? Sals Tax: Spcific or A Valorm Tax for a Non-rnwabl Rsourc? N. M. Hung 1 an N. V. Quyn 2 Absrac This papr shows ha for a im-inpnn spcific ax an a im-inpnn a valorm ax ha inuc h sam compiiv uilibrium in

More information

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract 866 Uni Naions Plaza i 566 Nw Yo NY 7 Phon: + 3 355 Fa: + 4 668 info@gach.com www.gach.com Eoan an Amican oions wih a singl amn of ivins Abo fomla Roll Gs & Whal Ma Ioff Absac Th aicl ovis a ivaion of

More information

Chemistry 988 Part 1

Chemistry 988 Part 1 Chmisry 988 Par 1 Radiaion Dcion & Masurmn Dp. of Chmisry --- Michigan Sa Univ. aional Suprconducing Cycloron Lab DJMorrissy Spring/2oo9 Cours informaion can b found on h wbsi: hp://www.chmisry.msu.du/courss/cm988uclar/indx.hml

More information

Chapter 17 Handout: Autocorrelation (Serial Correlation)

Chapter 17 Handout: Autocorrelation (Serial Correlation) Chapr 7 Handou: Auocorrlaion (Srial Corrlaion Prviw Rviw o Rgrssion Modl o Sandard Ordinary Las Squars Prmiss o Esimaion Procdurs Embddd wihin h Ordinary Las Squars (OLS Esimaion Procdur o Covarianc and

More information

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15]

S.Y. B.Sc. (IT) : Sem. III. Applied Mathematics. Q.1 Attempt the following (any THREE) [15] S.Y. B.Sc. (IT) : Sm. III Applid Mahmaics Tim : ½ Hrs.] Prlim Qusion Papr Soluion [Marks : 75 Q. Amp h following (an THREE) 3 6 Q.(a) Rduc h mari o normal form and find is rank whr A 3 3 5 3 3 3 6 Ans.:

More information

Empirical Process Theory

Empirical Process Theory Empirical Process heory 4.384 ime Series Analysis, Fall 27 Reciaion by Paul Schrimpf Supplemenary o lecures given by Anna Mikusheva Ocober 7, 28 Reciaion 7 Empirical Process heory Le x be a real-valued

More information

Chapter 2 The Derivative Applied Calculus 107. We ll need a rule for finding the derivative of a product so we don t have to multiply everything out.

Chapter 2 The Derivative Applied Calculus 107. We ll need a rule for finding the derivative of a product so we don t have to multiply everything out. Chaper The Derivaive Applie Calculus 107 Secion 4: Prouc an Quoien Rules The basic rules will le us ackle simple funcions. Bu wha happens if we nee he erivaive of a combinaion of hese funcions? Eample

More information

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35 MATH 5 PS # Summr 00.. Diffrnial Equaions and Soluions PS.# Show ha ()C #, 4, 7, 0, 4, 5 ( / ) is a gnral soluion of h diffrnial quaion. Us a compur or calculaor o skch h soluions for h givn valus of h

More information

Higher-Dimensional Kloosterman Sums and the Greatest Prime Factor of Integers of the Form a 1 a 2 a k+1 + 1

Higher-Dimensional Kloosterman Sums and the Greatest Prime Factor of Integers of the Form a 1 a 2 a k+1 + 1 Highr-Dimnsional Kloosrman Sums and h Gras Prim Facor of Ingrs of h Form a a a k+ + by Shngli Wu A hsis rsnd o h Univrsiy of Warloo in fulfilmn of h hsis rquirmn for h dgr of Docor of Philosohy in Pur

More information

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if.

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if. Tranform Mhod and Calculu of Svral Variabl H7, p Lcurr: Armin Halilovic KTH, Campu Haning E-mail: armin@dkh, wwwdkh/armin REPETITION bfor h am PART, Tranform Mhod Laplac ranform: L Driv h formula : a L[

More information

CHAPTER 9 Compressible Flow

CHAPTER 9 Compressible Flow CHPTER 9 Comrssibl Flow Char 9 / Comrssibl Flow Inroducion 9. c c cv + R. c kcv. c + R or c R k k Rk c k Sd of Sound 9.4 Subsiu Eq. 4.5.8 ino Eq. 4.5.7 and nglc onial nrgy chang: Q WS + + u~ u~. m ρ ρ

More information

Lecture 2: Current in RC circuit D.K.Pandey

Lecture 2: Current in RC circuit D.K.Pandey Lcur 2: urrn in circui harging of apacior hrough Rsisr L us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R and a ky K in sris. Whn h ky K is swichd on, h charging

More information

Frequency Response. Response of an LTI System to Eigenfunction

Frequency Response. Response of an LTI System to Eigenfunction Frquncy Rsons Las m w Rvsd formal dfnons of lnary and m-nvaranc Found an gnfuncon for lnar m-nvaran sysms Found h frquncy rsons of a lnar sysm o gnfuncon nu Found h frquncy rsons for cascad, fdbac, dffrnc

More information

LaPlace Transform in Circuit Analysis

LaPlace Transform in Circuit Analysis LaPlac Tranform in Circui Analyi Obciv: Calcula h Laplac ranform of common funcion uing h dfiniion and h Laplac ranform abl Laplac-ranform a circui, including componn wih non-zro iniial condiion. Analyz

More information

Fourier Series and Parseval s Relation Çağatay Candan Dec. 22, 2013

Fourier Series and Parseval s Relation Çağatay Candan Dec. 22, 2013 Fourir Sris nd Prsvl s Rlion Çğy Cndn Dc., 3 W sudy h m problm EE 3 M, Fll3- in som dil o illusr som conncions bwn Fourir sris, Prsvl s rlion nd RMS vlus. Q. ps h signl sin is h inpu o hlf-wv rcifir circui

More information

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is

Phys463.nb Conductivity. Another equivalent definition of the Fermi velocity is 39 Anohr quival dfiniion of h Fri vlociy is pf vf (6.4) If h rgy is a quadraic funcion of k H k L, hs wo dfiniions ar idical. If is NOT a quadraic funcion of k (which could happ as will b discussd in h

More information

Consider a system of 2 simultaneous first order linear equations

Consider a system of 2 simultaneous first order linear equations Soluon of sysms of frs ordr lnar quaons onsdr a sysm of smulanous frs ordr lnar quaons a b c d I has h alrna mar-vcor rprsnaon a b c d Or, n shorhand A, f A s alrady known from con W know ha h abov sysm

More information

BSWithJump Model And Pricing Of Quanto CDS With FX Devaluation Risk

BSWithJump Model And Pricing Of Quanto CDS With FX Devaluation Risk MPRA Mnich Prsonal RPEc Archiv BSWihmp Mol An Pricing Of Qano CDS Wih FX Dvalaion Risk Rachi EL-Mohammai Bank Of Amrical Mrrill Lynch Ocobr 9 Onlin a hps:mpra.b.ni-mnchn.478 MPRA Papr No. 478, pos 8. Novmbr

More information

EE 434 Lecture 22. Bipolar Device Models

EE 434 Lecture 22. Bipolar Device Models EE 434 Lcur 22 Bipolar Dvic Modls Quiz 14 Th collcor currn of a BJT was masurd o b 20mA and h bas currn masurd o b 0.1mA. Wha is h fficincy of injcion of lcrons coming from h mir o h collcor? 1 And h numbr

More information

Delay Dependent Exponential Stability and. Guaranteed Cost of Time-Varying Delay. Singular Systems

Delay Dependent Exponential Stability and. Guaranteed Cost of Time-Varying Delay. Singular Systems Ali amaical Scincs, ol. 6,, no. 4, 5655-5666 Dlay Dnn onnial Sabiliy an Guaran Cos of im-arying Dlay Singular Sysms Norin Caibi, l Houssain issir an Ablaziz Hmam LSSI. Darmn of Pysics, Faculy of Scincs,

More information

3(8 ) (8 x x ) 3x x (8 )

3(8 ) (8 x x ) 3x x (8 ) Scion - CHATER -. a d.. b. d.86 c d 8 d d.9997 f g 6. d. d. Thn, = ln. =. =.. d Thn, = ln.9 =.7 8 -. a d.6 6 6 6 6 8 8 8 b 9 d 6 6 6 8 c d.8 6 6 6 6 8 8 7 7 d 6 d.6 6 6 6 6 6 6 8 u u u u du.9 6 6 6 6 6

More information

Robert Kollmann. 6 September 2017

Robert Kollmann. 6 September 2017 Appendix: Supplemenary maerial for Tracable Likelihood-Based Esimaion of Non- Linear DSGE Models Economics Leers (available online 6 Sepember 207) hp://dx.doi.org/0.06/j.econle.207.08.027 Rober Kollmann

More information

Nikesh Bajaj. Fourier Analysis and Synthesis Tool. Guess.? Question??? History. Fourier Series. Fourier. Nikesh Bajaj

Nikesh Bajaj. Fourier Analysis and Synthesis Tool. Guess.? Question??? History. Fourier Series. Fourier. Nikesh Bajaj Guss.? ourir Analysis an Synhsis Tool Qusion??? niksh.473@lpu.co.in Digial Signal Procssing School of Elcronics an Communicaion Lovly Profssional Univrsiy Wha o you man by Transform? Wha is /Transform?

More information

16.512, Rocket Propulsion Prof. Manuel Martinez-Sanchez Lecture 3: Ideal Nozzle Fluid Mechanics

16.512, Rocket Propulsion Prof. Manuel Martinez-Sanchez Lecture 3: Ideal Nozzle Fluid Mechanics 6.5, Rok ropulsion rof. nul rinz-snhz Lur 3: Idl Nozzl luid hnis Idl Nozzl low wih No Sprion (-D) - Qusi -D (slndr) pproximion - Idl gs ssumd ( ) mu + Opimum xpnsion: - or lss, >, ould driv mor forwrd

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Chapter Three Systems of Linear Differential Equations

Chapter Three Systems of Linear Differential Equations Chaper Three Sysems of Linear Differenial Equaions In his chaper we are going o consier sysems of firs orer orinary ifferenial equaions. These are sysems of he form x a x a x a n x n x a x a x a n x n

More information

Stability Analysis of Three Species Model in Series Mutualism with Bionomic and Optimal Harvesting of Two Terminal Species

Stability Analysis of Three Species Model in Series Mutualism with Bionomic and Optimal Harvesting of Two Terminal Species Inrnaional Journal of Sinifi an Innovaiv Mahmaial Rsarh (IJSIMR) Volum, Issu, Dmbr, PP -5 ISS 7-7X (Prin) & ISS 7- (Onlin) www.arjournals.org Sabiliy nalysis of Thr Sis Mol in Sris Muualism wih Bionomi

More information