Ekpenyong Emmanuel John and Gideon Sunday N. x (2.1) International Journal of Statistics and Applied Mathematics 2018; 3(4): 60-64
|
|
- Phoebe Pope
- 5 years ago
- Views:
Transcription
1 Itrtol Jourl of Sttstcs d Appld Mtmtcs 8; ISSN Mts 8; Stts & Mts Rcvd Accptd Ekpyo Emmul Jo Dprtmt of Sttstcs Mcl Okpr Uvrsty of Arcultur Umudk Nr Gdo Sudy N Dprtmt of Sttstcs Ab Stt Polytcc Ab Nr Bys stmto of t sp prmtr of burr typ XII dstrbuto wt rlsd squrd rror loss d l loss fuctos udr som pror dstrbutos Ekpyo Emmul Jo d Gdo Sudy N Abstrct I ts ppr w obt som clsscl d Bys stmtors of t sp prmtrs of t Burr Typ XII dstrbuto. T Bys stmto ws md udr rlzd squrd rror loss fucto GSEF d lr potl INEX loss fuctos wt o-formtv pror Jffrys pror d formtv pror Gmm pror. ywords Bys stmto pror dstrbuto postror dstrbuto loss fucto d m squr rror. Itroducto Twlv dffrt forms of dstrbuto fuctos usful modl wd r of prmtl d bolocl dt forstry frctur rouss lf tst oprtol rsk tc wr troducd by Burr 94. Amo ts dstrbutos t Burr Typs III X d XII v ovr tm d mor rcoto d rtr pplcto rsrcs d ltrturs bcus of tr flblty d comptblty wt otr dstrbutos. For stc Burr typs III d XII ppromt svrl dstrbutos t fmls of o-orml dstrbutos s Burr 973; Rodruz 977; Tdkml 98 d Hdrck t l.. Burr Typ X dstrbuto s prtculrly mportt modll procsss wt rdully crs flur rt wtout y boud. It s lso ffctv modll strt dt d lf tm Surls d Pdtt. Svrl studs d b crrd out o Burr Typ XII dstrbuto wc clud u t l 7 Mkdoom d Jfr Solm t l P d Asd Sdu d Aslm 3 Al-Sr t l 4 J 4 d Tsum t l 5.Ts ppr focusd o Bys stmto of t sp prmtr of two-prmtr Burr Typ XII dstrbuto wt rspct to Grlzd Squr Error oss Fucto GSEF d r Epotl INEX loss fucto us Jffry s pror s o-formtv pror d mm pror s formtv pror wt t m of compr t prformc of t stmtors udr t two loss fuctos.. Clsscl Estmto of t Sp Prmtr of Burr Typ XII Dstrbuto Hr w cosdr tr mtods of clsscl stmto t Mmum klood Estmto ME Mmum M Squr Error MSE d t Uform Mmum Vrc Ubsd Estmto UMVUE. t X~Burr Typ XII α β t t probblty dsty fucto pdf of X s v by Corrspodc Ekpyo Emmul Jo Dprtmt of Sttstcs Mcl Okpr Uvrsty of Arcultur Umudk Nr f ; ~6~. wr α s t sp prmtr d β t scl prmtr. It c sly b sow tt. s vld pdf d t lo-lklood fucto s v by
2 Itrtol Jourl of Sttstcs d Appld Mtmtcs I I I I I. Tus w obt t ME s ˆ ME I wr I Rsd d Njm 4 vlutd t Mmum M Squr Error MMSE t clss of stmtors rprstd s. d obtd s.3 E E.4 Rsd d Njm 4 otd tt sc. s t fmly of potl dstrbuto; t mpls tt s Gmm dstrbuto wt prmtrs d α. ~G. α. Hc E d E. Substtut ts pcttos.4 mply d tus t MMSE of s; ˆ MMSE.5 I Bsd o m-scff s torm s ubsd stmt of α sc E d s suc s complt suffct sttstc for α. Trfor t UMVUE of α s v by ˆ UMVUE.6 I Yrmommd d Pzr drvd t M Squr Error MSE of t tr clsscl stmtors d lso sowd tt MSE ˆ MSE ˆ MSE ˆ MMSE UMVUE ME 3. Bys Estmto of t Sp Prmtr of Burr Typ XII Dstrbuto Bys stmto volvs t stmto of ukow prmtr wc s rrdd s rdom vrbl from v probblty dstrbuto. Ts c b crrd out us o-formtv pror dstrbuto Jffry pror or formtv pror dstrbuto of t prmtr of trst cosdrto of obsrvd dt sy... Howvr Jffry pror d mm pror dstrbuto wr cosdrd s o-formtv d formtv pror dstrbutos of t sp prmtr of Burr Typ XII dstrbuto d stmtos wr md udr GSEF d INEX oss Fucto. 3. T Postror Dstrbutos T o-formtv pror dstrbuto for α us Jffry pror s v by I wr s t Fsr formto dfd s 3. If I E 3. Tk t turl lo of. w v ~6~
3 ~6~ Itrtol Jourl of Sttstcs d Appld Mtmtcs I I I I If 3.3 T scod ordr prtl drvtv of 3.3 wt rspct to α vs If 3.4 Substtut 3.4 to 3. mpls I wc furtr mpls tt ; 3.5 obt t postror dsty fucto of α v Jffry s pror s ;... d d I I I I Tus t postror dstrbuto of α v Jffry s pror s Gmm wt prmtrs d. If t pror dstrbuto of s mm wt prmtrs d t t probblty dsty fucto pdf of s v by 3.7 Us 3.7 w obt t postror dstrbuto of s ;... d d I I I I Tus t postror dstrbuto of α v Gmm pror s Gmm wt prmtrs d. 3. Bys Estmto udr GSEF Rsd d Al Gz 4 v t Grlzd Squr Error oss fucto GSEF lθ θ s ˆ ˆ j j ;....3 d obtd stmtor for us t corrspod rsk fucto s θ = Eθ t+ Eθ t+ + Eθ + t + Eθ t+ + Eθ t 3.9 Substtut α for θ d for t 3.9 α = Eα + Eα + + Eα + + Eα + + Eα 3.
4 Itrtol Jourl of Sttstcs d Appld Mtmtcs T rsult 3.6 mpls tt Eα = d w Eα = + c substtut ts momts 3. vs t GSEF w stmtor for α us Jffry s pror α GSEFJ = w + + w + + +k+k + w k+ + w + + +k +k + w k = Γ++j j=o j I+ β j+ Γ Γ+j j=o j I+ β j Γ 3. From 3.8 Eα = +θ d +λ Eα = +θ+θ+ c t GSEF stmtor for α us mm pror +λ α GSEF = +θ w+λ + +θ++θ +θ+k+θ+k +θ++θ w+λ + + w+λ k+ +θ + w+λ + + +θ+k +θ+k +θ++θ w k = Γ+θ++j j=o j I+ β +λ j+ Γ+θ Γ+θ+j j=o j I+ β +λ j Γ+θ Bys Estmto udr INEX Rsd d Sult 5 ppld INEX loss fucto of t form ˆ b ˆ ˆ 3.3 wr b d obtd stmtor for θ us t rsk fucto s E l ˆ 3.4 Substtut α for θ 3.4 w v E l ˆ 3.5 Apply t rsult 3.6 w obtd stmtor for α udr INEX loss fucto wt Jffry s pror s follows; E.. d d 3.6 Substtut w v ˆ INEX j l l l l 3.7 Gv t postror dstrbuto 3.8 t INEX stmtor for α us mm pror s obtd s follows.. d E ~63~ d 3.8
5 Itrtol Jourl of Sttstcs d Appld Mtmtcs INEX l l l ˆ Cocluso I ts work w v b bl to drv t Bys stmtor of t sp prmtr of t Burr typ IX dstrbuto udr squrd rror loss d INEX fuctos wt Jffry s d Gmmα β prors. 5. Rfrcs. A-Sr AY Brt A Mous SA. Mrsl Olk Etdd Burr Typ XII Dstrbuto. Itrtol Jourl of Sttstcs d Probblty Burr I. Cumultv Frqucy Fuctos. Al of Mtmtcl Sttstcs. 94; Burr I. Prmtrs for Grl Systm of Dstrbuto to Mtc Grd of α 3 d α 4 Commucto Sttstcs-Tory d Mtods. 973; Hdrck TC Pt MD S Y. O Smult Uvrt d Multvrt Burr Typ III d Typ XII Dstrbutos. Appld Mtmtcl Scc. ; J DH. Bys Estmto of Burr Typ XII Bsd o Grl Prorssv Typ II Csor. Appld Mtmtcl Sccs. 4; Mkdoom I Jfr A. Bys Estmtos o Burr Typ XII Dstrbuto us Groupd d Uroupd. Austrl Jourl of Bsc d Appld Sccs. ; P H Asd S. Alyss of t Typ II Hybrd Csord Burr Typ XII Dstrbuto udr INEX oss Fucto. Appld Mtmtcl Sccs. ; Rsd HA AAlwy Al-Gz NA. Bys Estmto for t Rlblty Fucto of Prto Typ I Dstrbuto udr Grlzd Squr Error oss Fucto. Itrtol Jourl of Er d Iovtv Tcoloy IJEIT. 4; Rsd HA Al-Gz NA. Bys Estmtors for t Sp Prmtr of Prto Typ I Dstrbuto udr Grlzd Squr Error oss Fucto. Mtmtcl Tory d Modl. 4; Rsd HA Sult AJ. Bys Estmto of t Scl Prmtr for Ivrs Gmm Dstrbuto udr INEX oss Fucto. Itrtol Jourl of Advcd Rsrc. 5; Rodruz RN. A Gud to Burr Typ XII Dstrbutos Bomtrk. 977; Sdu TN Aslm M. Estmto of t Burr Typ VIII Dstrbuto trou Bys Frmwork Advcs Arts Socl Sccs d Educto Rsrc. 3; Solm AA Abd Ell AH Abou-Al NA. Bys Ifrc d Prdcto of Burr Typ XII Dstrbuto for Prorssv Frst Flur Csord Smpl. Itllt Iformto Mmt. ; Surls JG Pdtt J. Ifrc for Rlblty d Strss-Strt for Scld Burr Typ X Dstrbuto ftm Dt Alyss. ; Tdkml PR. A look o t Burr d Rltd Dstrbuto. Itrtol Sttstcl Rvw. 98; AlBldw TH Rsd HA Jsm SH. Us Grlzd Squr oss Fucto to Estmt t Sp Prmtr of t Burr Typ XII Dstrbuto. Itrtol Jourl of Advcd Rsrc. 5; u SJ C YJ C CT. Sttstcl Ifrc Bsd O Prorssvly Csord Smpls wt Rdom Rmovls from t Burr Typ XII Dstrbuto. Jourl of Sttstcl Computto d Smulto. 7; Yrmommd M Pzr H. Mm Estmto of t Prmtr of t Burr Typ XII Dstrbuto. Austrl Jourl of Bsc d Appld Sccs. ; ~64~
A note on Kumaraswamy Fréchet distribution
AENSI Jourls Austrl Jourl of Bsc d Appld Sccs ISSN:99-878 Jourl hom pg: wwwswcom A ot o Kumrswmy Frécht dstruto Md M E d 2 Ad-Eltw A R Dprtmt of Sttstcs Fculty of Commrc Zgzg Uvrsty Egypt 2 School of Busss
More informationERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**
ERDO-MARANDACHE NUMBER b Tbrc* Tt Tbrc** *Trslv Uvrsty of Brsov, Computr cc Dprtmt **Uvrsty of Mchstr, Computr cc Dprtmt Th strtg pot of ths rtcl s rprstd by rct work of Fch []. Bsd o two symptotc rsults
More informationMore Statistics tutorial at 1. Introduction to mathematical Statistics
Mor Sttstcs tutorl t wwwdumblttldoctorcom Itroducto to mthmtcl Sttstcs Fl Soluto A Gllup survy portrys US trprurs s " th mvrcks, drmrs, d lors whos rough dgs d ucompromsg d to do t thr ow wy st thm shrp
More informationStatistical properties and applications of a Weibull- Kumaraswamy distribution
Itrtol Jourl of Sttstcs d Appld Mthmtcs 208; 3(6): 8090 ISSN: 2456452 Mths 208; 3(6): 8090 208 Stts & Mths www.mthsjourl.com Rcvd: 09208 Accptd: 20208 Amu M Dprtmt Mths d Sttstcs, Aukr Ttr Al Polytchc,
More informationCHAPTER 4. FREQUENCY ESTIMATION AND TRACKING
CHPTER 4. FREQUENCY ESTITION ND TRCKING 4.. Itroducto Estmtg mult-frquc susodl sgls burd os hs b th focus of rsrch for qut som tm [68] [58] [46] [64]. ost of th publshd rsrch usd costrd ft mpuls rspos
More informationTHE TRANSMUTED GENERALIZED PARETO DISTRIBUTION. STATISTICAL INFERENCE AND SIMULATION RESULTS
Mr l Btr vl Admy Stf Bullt Volum VIII 5 Issu Pulshd y Mr l Btr vl Admy Prss Costt Rom // Th jourl s dd : PROQUST STh Jourls PROQUST grg Jourls PROQUST Illustrt: Thology PROQUST Thology Jourls PROQUST Mltry
More informationBayesian Shrinkage Estimator for the Scale Parameter of Exponential Distribution under Improper Prior Distribution
Itratoal Joural of Statstcs ad Applcatos, (3): 35-3 DOI:.593/j.statstcs.3. Baysa Shrkag Estmator for th Scal Paramtr of Expotal Dstrbuto udr Impropr Pror Dstrbuto Abbas Najm Salma *, Rada Al Sharf Dpartmt
More informationTOTAL LEAST SQUARES ALGORITHMS FOR FITTING 3D STRAIGHT LINES
IJMML 6: (07) 35-44 Mrch 07 ISSN: 394-58 vll t http://sctfcdvcsco DOI: http://ddoorg/0864/jmml_70088 OL LES SQURES LGORIHMS FOR FIING 3D SRIGH LINES Cupg Guo Juhu Pg d Chuto L School of Scc Ch Uvrst of
More informationReliability of time dependent stress-strength system for various distributions
IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,
More informationThe Research on Position and Orientation Constraint of Rootless Redundant Robots Based on Dynamic Modeling
rd Itrtol orc o chtrocs, Robotcs d Automto IRA 5 h Rsrch o Posto d Ortto ostrt o Rootlss Rdudt Robots Bsd o Dymc odl LI, *, JIA Hyo,b, XI Yzhou,c d ZHA Xp,d Dprtmt o chcl Elctrcl Er, Hb Arculturl Ursty,
More informationDifferential Entropy 吳家麟教授
Deretl Etropy 吳家麟教授 Deto Let be rdom vrble wt cumultve dstrbuto ucto I F s cotuous te r.v. s sd to be cotuous. Let = F we te dervtve s deed. I te s clled te pd or. Te set were > 0 s clled te support set
More informationExponentiated Weibull-Exponential Distribution with Applications
Avlbl t http://pvmudu/m Appl Appl Mth ISSN: 93-9466 Vol, Issu (Dcmb 07), pp 70-75 Applctos d Appld Mthmtcs: A Ittol Joul (AAM) Epottd Wbull-Epotl Dstbuto wth Applctos M Elghy, M Shkl d BM Golm Kb 3 Abstct
More information3.4 Properties of the Stress Tensor
cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato
More informationLinear Prediction Analysis of
Lr Prdcto Alyss of Sch Souds Brl Ch Drtt of Coutr Scc & Iforto grg Ntol Tw Norl Uvrsty frcs: X Hug t l So Lgug g Procssg Chtrs 5 6 J Dllr t l Dscrt-T Procssg of Sch Sgls Chtrs 4-6 3 J W Pco Sgl odlg tchqus
More informationBinary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit
(c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty 3 Bary Choc LPM logt logstc rgrso probt Multpl Choc Multomal Logt (c Pogsa Porchawssul,
More informationChapter 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 informationOPTIMAL STEP-STRESS PLANS FOR ACCELERATED LIFE TESTING CONSIDERING RELIABILITY/LIFE PREDICTION
OPIM P-R PN FOR CCRD IF ING CONIDRING RIBIIY/IF PRDICION Dssrtto Prstd b Chhu to h Dprtmt of Mhl d Idustrl grg prtl fulfllmt of th rqurmt for th dgr of Dotor of Phlosoph Idustrl grg Northstr Uvrst Bosto
More informationA Monotone Process Replacement Model for a Two Unit Cold Standby Repairable System
Itrtol Jorl of Egrg Rsrch d Dlopmt -ISS: 78-67 p-iss: 78-8 www.jrd.com Volm 7 Iss 8 J 3 PP. 4-49 A Mooto Procss Rplcmt Modl for Two Ut Cold Std Rprl Sstm Dr.B.Vt Rmd Prof.A. Mllrj Rdd M. Bhg Lshm 3 Assstt
More informationLinear Prediction Analysis of Speech Sounds
Lr Prdcto Alyss of Sch Souds Brl Ch 4 frcs: X Hug t l So Lgug Procssg Chtrs 5 6 J Dllr t l Dscrt-T Procssg of Sch Sgls Chtrs 4-6 3 J W Pco Sgl odlg tchqus sch rcogto rocdgs of th I Stbr 993 5-47 Lr Prdctv
More informationOutline. Outline. Outline. Questions 2010/9/30. Introduction The Multivariate Normal Density and Its Properties
9 Multvrt orml Dstruto Shyh-Kg Jg Drtmt of Eltrl Egrg Grdut Isttut of Commuto Grdut Isttut of tworkg d Multmd Outl Itroduto Th Multvrt orml Dsty d Its Prorts Smlg from Multvrt orml Dstruto d Mmum Lklhood
More informationA Class of Harmonic Meromorphic Functions of Complex Order
Borg Irol Jourl o D Mg Vol 2 No 2 Ju 22 22 A Clss o rmoc Mromorpc Fucos o Complx Ordr R Elrs KG Surm d TV Sudrs Asrc--- T sml work o Clu d Sl-Smll [3] o rmoc mppgs gv rs o suds o suclsss o complx-vlud
More informationCHAPTER 7. X and 2 = X
CHATR 7 Sco 7-7-. d r usd smors o. Th vrcs r d ; comr h S vrc hs cs / / S S Θ Θ Sc oh smors r usd mo o h vrcs would coclud h s h r smor wh h smllr vrc. 7-. [ ] Θ 7 7 7 7 7 7 [ ] Θ ] [ 7 6 Boh d r usd sms
More informationAccuracy of ADC dynamic parameters measurement. Jiri Brossmann, Petr Cesak, Jaroslav Roztocil
ccurcy o dymc prmtrs msurmt Jr Brossm Ptr Csk Jroslv Roztocl Czch Tchcl Uvrsty Prgu Fculty o Elctrcl Egrg Tchck CZ-667 Prgu 6 Czch Rpublc Pho: 40-4 35 86 Fx: 40-33 339 9 E-ml: jr.brossm@gml.com cskp@l.cvut.cz
More informationOutline. Outline. Outline. Questions. Multivariate Normal Distribution. Multivariate Normal Distribution
Multvrt orml Dstruto hyh-kg Jg Drtmt of Eltrl Egrg Grdut sttut of Commuto Grdut sttut of tworg d Multmd Outl troduto Th Multvrt orml Dsty d ts Prorts mlg from Multvrt orml Dstruto d Mmum Llhood Estmto
More informationThe University of Sydney MATH 2009
T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n
More informationDivided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano
RIGHT-ANGLE WEAVE Dv mons Mm t look o ts n rlt tt s ptvly p sn y Py Brnkmn Mttlno Dv your mons nto trnls o two or our olors. FCT-SCON0216_BNB66 2012 Klm Pulsn Co. Ts mtrl my not rprou n ny orm wtout prmsson
More informationTHE EXPONENTIATED GENERALIZED FLEXIBLE WEIBULL EXTENSION DISTRIBUTION
Fudmtl Joul of Mthmtcs d Mthmtcl Sccs Vol. 6 Issu 6 Pgs 75-98 Ths pp s vll ol t http://www.fdt.com/ Pulshd ol Octo 6 THE EXPONENTIATED GENERAIZED FEXIBE WEIBU EXTENSION DISTRIBUTION ABDEFATTAH MUSTAFA
More informationAlmost Unbiased Estimation of the Poisson Regression Model
Ecoometrcs Worg Pper EWP0909 ISSN 485-644 Deprtmet of Ecoomcs Almost Ubsed Estmto of the Posso Regresso Model Dvd E. Gles Deprtmet of Ecoomcs, Uversty of Vctor Vctor, BC, Cd V8W Y & Hu Feg Deprtmet of
More informationComputer Graphics. Viewing & Projections
Vw & Ovrvw rr : rss r t -vw trsrt: st st, rr w.r.t. r rqurs r rr (rt syst) rt: 2 trsrt st, rt trsrt t 2D rqurs t r y rt rts ss Rr P usuy st try trsrt t wr rts t rs t surs trsrt t r rts u rt w.r.t. vw vu
More information5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees
/1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our
More informationOn Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data
saqartvlos mcrbata rovul akadms moamb, t 9, #2, 2015 BULLETIN OF THE GEORGIAN NATIONAL ACADEMY OF SCIENCES, vol 9, o 2, 2015 Mathmatcs O Estmato of Ukow Paramtrs of Epotal- Logarthmc Dstrbuto by Csord
More informationSuzan Mahmoud Mohammed Faculty of science, Helwan University
Europa Joural of Statstcs ad Probablty Vol.3, No., pp.4-37, Ju 015 Publshd by Europa Ctr for Rsarch Trag ad Dvlopmt UK (www.ajourals.org ESTIMATION OF PARAMETERS OF THE MARSHALL-OLKIN WEIBULL DISTRIBUTION
More informationPlanar convex hulls (I)
Covx Hu Covxty Gv st P o ots 2D, tr ovx u s t sst ovx oyo tt ots ots o P A oyo P s ovx or y, P, t st s try P. Pr ovx us (I) Coutto Gotry [s 3250] Lur To Bowo Co ovx o-ovx 1 2 3 Covx Hu Covx Hu Covx Hu
More informationUnbalanced Panel Data Models
Ubalacd Pal Data odls Chaptr 9 from Baltag: Ecoomtrc Aalyss of Pal Data 5 by Adrás alascs 4448 troducto balacd or complt pals: a pal data st whr data/obsrvatos ar avalabl for all crosssctoal uts th tr
More informationELECTRONIC SUPPLEMENTARY INFORMATION
Elctronc Supplmntry Mtrl (ESI) or Polymr Cmstry. Ts ournl s T Royl Socty o Cmstry 2015 ELECTRONIC SUPPLEMENTARY INFORMATION Poly(lyln tcont)s An ntrstn clss o polystrs wt proclly loct xo-cn oul ons suscptl
More informationPredicting Survival Outcomes Based on Compound Covariate Method under Cox Proportional Hazard Models with Microarrays
Predctg Survvl Outcomes Bsed o Compoud Covrte Method uder Cox Proportol Hzrd Models wth Mcrorrys PLoS ONE 7(10). do:10.1371/ourl.poe.0047627. http://dx.plos.org/10.1371/ourl.poe.0047627 Tkesh Emur Grdute
More informationCMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017
Rn: Not ovr n or rns. CMSC 451: Ltr 4 Brs n 2-E Conntvty Trsy, Sp 7, 2017 Hr-Orr Grp Conntvty: (T ollown mtrl ppls only to nrt rps!) Lt G = (V, E) n onnt nrt rp. W otn ssm tt or rps r onnt, t somtms t
More informationJOURNAL OF COLLEGE OF EDUCATION NO
NO.3...... 07 Ivrt S-bst Copproxmto -ormd Spcs Slw Slm bd Dprtmt of Mthmtcs Collg of ducto For Pur scc, Ib l-hthm, Uvrsty of Bghdd slwlbud@yhoo.com l Musddk Dlph Dprtmt of Mthmtcs,Collg of Bsc ducto, Uvrsty
More informationSome Unbiased Classes of Estimators of Finite Population Mean
Itertol Jourl O Mtemtcs Ad ttstcs Iveto (IJMI) E-IN: 3 4767 P-IN: 3-4759 Www.Ijms.Org Volume Issue 09 etember. 04 PP-3-37 ome Ubsed lsses o Estmtors o Fte Poulto Me Prvee Kumr Msr d s Bus. Dertmet o ttstcs,
More information1. Stefan-Boltzmann law states that the power emitted per unit area of the surface of a black
Stf-Boltzm lw stts tht th powr mttd pr ut r of th surfc of blck body s proportol to th fourth powr of th bsolut tmprtur: 4 S T whr T s th bsolut tmprtur d th Stf-Boltzm costt= 5 4 k B 3 5c h ( Clcult 5
More informationIn which direction do compass needles always align? Why?
AQA Trloy Unt 6.7 Mntsm n Eltromntsm - Hr 1 Complt t p ll: Mnt or s typ o or n t s stronst t t o t mnt. Tr r two typs o mnt pol: n. Wrt wt woul ppn twn t pols n o t mnt ntrtons low: Drw t mnt l lns on
More informationRISK-NEUTRAL DENSITIES IN ENTROPY THEORY OF STOCK OPTIONS USING LAMBERT FUNCTION AND A NEW APPROACH
H PUBLHNG HOU PROCDNG OF H ROMANAN ACADM rs A OF H ROMANAN ACADM Volm 6 Nmbr /00x pp 0 7 RK-NURAL DN N NROP HOR OF OCK OPON UNG LAMBR FUNCON AND A N APPROACH Vsl PRDA Mhmmd HRAZ Uvrst of Bchrst Fclt of
More informationME 501A Seminar in Engineering Analysis Page 1
St Ssts o Ordar Drtal Equatos Novbr 7 St Ssts o Ordar Drtal Equatos Larr Cartto Mcacal Er 5A Sar Er Aalss Novbr 7 Outl Mr Rsults Rvw last class Stablt o urcal solutos Stp sz varato or rror cotrol Multstp
More informationThree-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations
Appld Mathmatcal Sccs ol. 9 5 o. 43 75-73 HKAR Ltd www.m-hkar.com http://dx.do.org/.988/ams.5.567 Thr-Dmsoal Thory of Nolar-Elastc Bods Stablty udr Ft Dformatos Yu.. Dmtrko Computatoal Mathmatcs ad Mathmatcal
More informationβ (cf Khan, 2006). In this model, p independent
Proc. ICCS-3, Bogor, Idoes December 8-4 Vol. Testg the Equlty of the Two Itercets for the Prllel Regresso Model Bud Prtko d Shhjh Kh Dertmet of Mthemtcs d Nturl Scece Jederl Soedrm Uversty, Purwokerto,
More informationBayesian Test for Lifetime Performance Index of Ailamujia Distribution Under Squared Error Loss Function
Pur ad Appld Mathmatcs Joural 6; 5(6): 8-85 http://www.sccpublshggroup.com/j/pamj do:.648/j.pamj.656. ISSN: 36-979 (Prt); ISSN: 36-98 (Ol) Baysa Tst for ftm Prformac Idx of Alamuja Dstrbuto Udr Squard
More informationIrregular Boundary Area Computation. by Quantic Hermite Polynomial
It. J. Cotmp. Mat. Sccs, Vol. 6,, o., - Irrgular Boudar Ara Computato b Quatc Hrmt Polomal J. Karwa Hama Faraj, H.-S. Faradu Kadr ad A. Jamal Muamad Uvrst of Sulama-Collg of Scc Dpartmt of Matmatcs, Sualma,
More information4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling.
Cptr 4 4 Intrvl Suln Gry Alortms Sls y Kvn Wyn Copyrt 005 Prson-Ason Wsly All rts rsrv Intrvl Suln Intrvl Suln: Gry Alortms Intrvl suln! Jo strts t s n nss t! Two os omptl ty on't ovrlp! Gol: n mxmum sust
More informationIFYFM002 Further Maths Appendix C Formula Booklet
Ittol Foudto Y (IFY) IFYFM00 Futh Mths Appd C Fomul Booklt Rltd Documts: IFY Futh Mthmtcs Syllbus 07/8 Cotts Mthmtcs Fomul L Equtos d Mtcs... Qudtc Equtos d Rmd Thom... Boml Epsos, Squcs d Ss... Idcs,
More informationLecture 20: Minimum Spanning Trees (CLRS 23)
Ltur 0: Mnmum Spnnn Trs (CLRS 3) Jun, 00 Grps Lst tm w n (wt) rps (unrt/rt) n ntrou s rp voulry (vrtx,, r, pt, onnt omponnts,... ) W lso suss jny lst n jny mtrx rprsntton W wll us jny lst rprsntton unlss
More informationA METHOD FOR NUMERICAL EVALUATING OF INVERSE Z-TRANSFORM UDC 519.6(045)
FACTA UNIVERSITATIS Srs: Mcacs Automatc Cotrol ad Rootcs Vol 4 N o 6 4 pp 33-39 A METHOD FOR NUMERICAL EVALUATING OF INVERSE Z-TRANSFORM UDC 59645 Prdrag M Raovć Momr S Staovć Slađaa D Marovć 3 Dpartmt
More informationLECTURE 6 TRANSFORMATION OF RANDOM VARIABLES
LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt
More informationn r t d n :4 T P bl D n, l d t z d th tr t. r pd l
n r t d n 20 20 :4 T P bl D n, l d t z d http:.h th tr t. r pd l 2 0 x pt n f t v t, f f d, b th n nd th P r n h h, th r h v n t b n p d f r nt r. Th t v v d pr n, h v r, p n th pl v t r, d b p t r b R
More informationInfluence of Pareto optimality on the Maximum Entropy Methods
Ifluc of Prto optmlt o th Mmum Etrop Mthods Srhr Pddvrpu Gujjlpud Vkt S Sul d Rghurm S School of Mchcl Egrg SASTRA Uvrst Thjvur Tml du-60 Corrspodg uthor: srhr@mch.sstr.du gvssul997@sstr.c. Astrct. Glrk
More informationTh n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v
Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v ll f x, h v nd d pr v n t fr tf l t th f nt r n r
More informationThe probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1
Th robablty of Ra's hyothss bg tru s ual to Yuyag Zhu Abstract Lt P b th st of all r ubrs P b th -th ( ) lt of P ascdg ordr of sz b ostv tgrs ad s a rutato of wth Th followg rsults ar gv ths ar: () Th
More information8(4 m0) ( θ ) ( ) Solutions for HW 8. Chapter 25. Conceptual Questions
Solutios for HW 8 Captr 5 Cocptual Qustios 5.. θ dcrass. As t crystal is coprssd, t spacig d btw t plas of atos dcrass. For t first ordr diffractio =. T Bragg coditio is = d so as d dcrass, ust icras for
More informationMODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f
MODEL QUESTION Statstcs (Thory) (Nw Syllabus) GROUP A d θ. ) Wrt dow th rsult of ( ) ) d OR, If M s th mod of a dscrt robablty dstrbuto wth mass fucto f th f().. at M. d d ( θ ) θ θ OR, f() mamum valu
More informationI N A C O M P L E X W O R L D
IS L A M I C E C O N O M I C S I N A C O M P L E X W O R L D E x p l o r a t i o n s i n A g-b eanste d S i m u l a t i o n S a m i A l-s u w a i l e m 1 4 2 9 H 2 0 0 8 I s l a m i c D e v e l o p m e
More informationAlmost unbiased exponential estimator for the finite population mean
Almos ubasd poal smaor for f populao ma Rajs Sg, Pakaj aua, ad rmala Saa, Scool of Sascs, DAVV, Idor (M.P., Ida (rsgsa@aoo.com Flor Smaradac ar of Dparm of Mamacs, Uvrs of Mco, Gallup, USA (smarad@um.du
More informationOn Hamiltonian Tetrahedralizations Of Convex Polyhedra
O Ht Ttrrzts O Cvx Pyr Frs C 1 Q-Hu D 2 C A W 3 1 Dprtt Cputr S T Uvrsty H K, H K, C. E: @s.u. 2 R & TV Trsss Ctr, Hu, C. E: q@163.t 3 Dprtt Cputr S, Mr Uvrsty Nwu St. J s, Nwu, C A1B 35. E: w@r.s.u. Astrt
More informationSecond Handout: The Measurement of Income Inequality: Basic Concepts
Scod Hadout: Th Masurmt of Icom Iqualty: Basc Cocpts O th ormatv approach to qualty masurmt ad th cocpt of "qually dstrbutd quvalt lvl of com" Suppos that that thr ar oly two dvduals socty, Rachl ad Mart
More informationSYSTEMS OF LINEAR EQUATIONS
SYSES OF INER EQUIONS Itroducto Emto thods Dcomposto thods tr Ivrs d Dtrmt Errors, Rsdus d Codto Numr Itrto thods Icompt d Rdudt Systms Chptr Systms of r Equtos /. Itroducto h systm of r qutos s formd
More informationProperties of Demand
AGEC 5733 LECTURE NOTES DR. SHIDA HENNEBERR ROERTIES OF DEMAND AGEC 5733 cl ot /4 /9 d / rort of Dmd Grl rort of Dmd:. El Arto. Homoty 3. Courot d 4. Symmtry Mtr of Eltct M α α M M α L LL M M wr dtur Q
More informationDual to Separate Ratio Type Exponential Estimator in Post-Stratification
J tt Appl Pro 3, o 3, 5-3 (0 5 Jourl of ttistics Applictios & Probbilit A Itrtiol Jourl ttp://ddoiorg/0785/jsp/03033 Dul to prt Rtio Tp Epotil Estimtor i Post-trtifictio Hill A o d Rjs Tilor cool of tudis
More informationCMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk
CMPS 2200 Fll 2017 Grps Crol Wnk Sls ourtsy o Crls Lsrson wt ns n tons y Crol Wnk 10/23/17 CMPS 2200 Intro. to Alortms 1 Grps Dnton. A rt rp (rp) G = (V, E) s n orr pr onsstn o st V o vrts (snulr: vrtx),
More informationA Measure of Inaccuracy between Two Fuzzy Sets
LGRN DEMY OF SENES YERNETS ND NFORMTON TEHNOLOGES Volum No 2 Sofa 20 Masur of accuracy btw Two Fuzzy Sts Rajkumar Vrma hu Dv Sharma Dpartmt of Mathmatcs Jayp sttut of formato Tchoy (Dmd vrsty) Noda (.P.)
More informationChapter 5 Special Discrete Distributions. Wen-Guey Tzeng Computer Science Department National Chiao University
Chatr 5 Scal Dscrt Dstrbutos W-Guy Tzg Comutr Scc Dartmt Natoal Chao Uvrsty Why study scal radom varabls Thy aar frqutly thory, alcatos, statstcs, scc, grg, fac, tc. For aml, Th umbr of customrs a rod
More informationSpecial Curves of 4D Galilean Space
Irol Jourl of Mhml Egrg d S ISSN : 77-698 Volum Issu Mrh hp://www.jms.om/ hps://ss.googl.om/s/jmsjourl/ Spl Curvs of D ll Sp Mhm Bkş Mhmu Ergü Alpr Osm Öğrmş Fır Uvrsy Fuly of S Dprm of Mhms 9 Elzığ Türky
More informationPriority Search Trees - Part I
.S. 252 Pro. Rorto Taassa oputatoal otry S., 1992 1993 Ltur 9 at: ar 8, 1993 Sr: a Q ol aro Prorty Sar Trs - Part 1 trouto t last ltur, w loo at trval trs. or trval pot losur prols, ty us lar spa a optal
More informationBayesian Approach to Generalized Normal Distribution under Non- Informative and Informative Priors
I.J. Mtmtc Sccs d Comutg 8 9- Pusd O Novm 8 MCS (tt://www.mcs-ss.t) DOI:.585/jmsc.8.. Av o t tt://www.mcs-ss.t/jmsc Bys Aoc to Gd Nom Dstuto ud No- Ifomtv d Ifomtv Pos Sm Nqs * S.P.Amd Aqu Amd Dtmt of
More information4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n, h r th ff r d nd
n r t d n 20 20 0 : 0 T P bl D n, l d t z d http:.h th tr t. r pd l 4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n,
More informationA L A BA M A L A W R E V IE W
A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N
More informationEfficient Computations for Evaluating Extended Stochastic Petri Nets using Algebraic Operations
Itrtol Jourl of Cotrol Automto d Sytm Vol No 4 Dcmbr 4 Effct Computto for Evlutg Extdd Stochtc Ptr Nt ug Algbrc Oprto Dog-Sug Km Hog-Ju Moo J-Hyog Bh Woo Hyu Kwo d Zygmut J H Abtrct: Th ppr prt ffct mthod
More informationIntroduction 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 informationA COMPARISON OF SEVERAL TESTS FOR EQUALITY OF COEFFICIENTS IN QUADRATIC REGRESSION MODELS UNDER HETEROSCEDASTICITY
Colloquum Bomtrcum 44 04 09 7 COMPISON OF SEVEL ESS FO EQULIY OF COEFFICIENS IN QUDIC EGESSION MODELS UNDE HEEOSCEDSICIY Małgorzata Szczpa Dorota Domagała Dpartmt of ppld Mathmatcs ad Computr Scc Uvrsty
More informationImproving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e)
POW CSE 36: Dt Struturs Top #10 T Dynm (Equvln) Duo: Unon-y-Sz & Pt Comprsson Wk!! Luk MDowll Summr Qurtr 003 M! ZING Wt s Goo Mz? Mz Construton lortm Gvn: ollton o rooms V Conntons twn t rooms (ntlly
More informationIntroduction to Laplace Transforms October 25, 2017
Iroduco o Lplc Trform Ocobr 5, 7 Iroduco o Lplc Trform Lrr ro Mchcl Egrg 5 Smr Egrg l Ocobr 5, 7 Oul Rvw l cl Wh Lplc rform fo of Lplc rform Gg rform b gro Fdg rform d vr rform from bl d horm pplco o dffrl
More informationQuantum Harmonic Oscillator
Quu roc Oscllor Quu roc Oscllor 6 Quu Mccs Prof. Y. F. C Quu roc Oscllor Quu roc Oscllor D S..O.:lr rsorg forc F k, k s forc cos & prbolc pol. V k A prcl oscllg roc pol roc pol s u po of sbly sys 6 Quu
More informationMultiple-Choice Test Runge-Kutta 4 th Order Method Ordinary Differential Equations COMPLETE SOLUTION SET
Multpl-Co Tst Rung-Kutta t Ordr Mtod Ordnar Drntal Equatons COMPLETE SOLUTION SET. To solv t ordnar drntal quaton sn ( Rung-Kutta t ordr mtod ou nd to rwrt t quaton as (A sn ( (B ( sn ( (C os ( (D sn (
More informationP a g e 5 1 of R e p o r t P B 4 / 0 9
P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e
More information,. *â â > V>V. â ND * 828.
BL D,. *â â > V>V Z V L. XX. J N R â J N, 828. LL BL D, D NB R H â ND T. D LL, TR ND, L ND N. * 828. n r t d n 20 2 2 0 : 0 T http: hdl.h ndl.n t 202 dp. 0 02802 68 Th N : l nd r.. N > R, L X. Fn r f,
More informationUniversity of Washington Department of Chemistry Chemistry 453 Winter Quarter 2014 Lecture 20: Transition State Theory. ERD: 25.14
Univrsity of Wasinton Dpartmnt of Cmistry Cmistry 453 Wintr Quartr 04 Lctur 0: Transition Stat Tory. ERD: 5.4. Transition Stat Tory Transition Stat Tory (TST) or ctivatd Complx Tory (CT) is a raction mcanism
More informationOn the Existence and uniqueness for solution of system Fractional Differential Equations
OSR Jourl o Mhms OSR-JM SSN: 78-578. Volum 4 ssu 3 Nov. - D. PP -5 www.osrjourls.org O h Es d uquss or soluo o ssm rol Drl Equos Mh Ad Al-Wh Dprm o Appld S Uvrs o holog Bghdd- rq Asr: hs ppr w d horm o
More informationLinear Algebra Existence of the determinant. Expansion according to a row.
Lir Algbr 2270 1 Existc of th dtrmit. Expsio ccordig to row. W dfi th dtrmit for 1 1 mtrics s dt([]) = (1) It is sy chck tht it stisfis D1)-D3). For y othr w dfi th dtrmit s follows. Assumig th dtrmit
More informationCBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane.
CBSE CBSE SET- SECTION. Gv tht d W d to fd 7 7 Hc, 7 7 7. Lt,. W ow tht.. Thus,. Cosd th vcto quto of th pl.. z. - + z = - + z = Thus th Cts quto of th pl s - + z = Lt d th dstc tw th pot,, - to th pl.
More informationRe-synthesis for Delay Variation Tolerance
49.1 R-sytss or Dly Vrto Tolr S-C C Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw s@s.tu.u.tw C-To Hs Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw s@tu.s.tu.u.tw K-C Wu Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw Alx@tu.s.tu.u.tw
More informationFace Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction
F Dtto Roto Lr Alr F Roto C Y I Ursty O solto: tto o l trs s s ys os ot. Dlt to t to ltpl ws. F Roto Aotr ppro: ort y rry s tor o so E.. 56 56 > pot 6556- stol sp A st o s t ps to ollto o pots ts sp. F
More informationQuantitative Genomics and Genetics BTRY 4830/6830; PBSB
Quntttv Gnomcs n Gntcs BTRY 4830/6830; BSB.520.0 Lctur8: Logstc rgrsson II Json Mzy jgm45@cornll.u Aprl 0, 208 (T 8:40-9:55 Announcmnts Grng (homworks n mtrm rojct wll b ssgn NEXT WEEK (!! Schul for th
More informationD t r l f r th n t d t t pr p r d b th t ff f th l t tt n N tr t n nd H n N d, n t d t t n t. n t d t t. h n t n :.. vt. Pr nt. ff.,. http://hdl.handle.net/2027/uiug.30112023368936 P bl D n, l d t z d
More informationLet's revisit conditional probability, where the event M is expressed in terms of the random variable. P Ax x x = =
L's rvs codol rol whr h v M s rssd rs o h rdo vrl. L { M } rrr v such h { M } Assu. { } { A M} { A { } } M < { } { } A u { } { } { A} { A} ( A) ( A) { A} A A { A } hs llows us o cosdr h cs wh M { } [ (
More informationOdd Generalized Exponential Flexible Weibull Extension Distribution
Odd Gralzd Epotal Flbl Wbull Etso Dstrbuto Abdlfattah Mustafa Mathmatcs Dpartmt Faculty of Scc Masoura Uvrsty Masoura Egypt abdlfatah mustafa@yahoo.com Bh S. El-Dsouy Mathmatcs Dpartmt Faculty of Scc Masoura
More informationNew Error Model of Entropy Encoding for Image Compression
Wb St: www.jttcs.org Eml: dtor@jttcs.org, dtorjttcs@gml.com Volum, Issu, Mrch Aprl 03 ISSN 78-6856 Nw Error Modl of Etropy Ecodg for Img Comprsso Moht Mshr, Rjsh Tjw, Assstt Profssor Ary Collg of Egrg
More informationNHPP and S-Shaped Models for Testing the Software Failure Process
Irol Jourl of Ls Trds Copug (E-ISSN: 45-5364 8 Volu, Issu, Dcr NHPP d S-Shpd Modls for Tsg h Sofwr Flur Procss Dr. Kr Arr Asss Profssor K.J. Soy Isu of Mg Suds & Rsrch Vdy Ngr Vdy Vhr Mu. Id. dshuh_3@yhoo.co/rrr@ssr.soy.du
More informationDepartment of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis
Dpartmt of Mathmatcs ad Statstcs Ida Isttut of Tchology Kapur MSOA/MSO Assgmt 3 Solutos Itroducto To omplx Aalyss Th problms markd (T) d a xplct dscusso th tutoral class. Othr problms ar for hacd practc..
More informationMajor: All Engineering Majors. Authors: Autar Kaw, Luke Snyder
Nolr Rgrsso Mjor: All Egrg Mjors Auhors: Aur Kw, Luk Sydr hp://urclhodsgusfdu Trsforg Nurcl Mhods Educo for STEM Udrgrdus 3/9/5 hp://urclhodsgusfdu Nolr Rgrsso hp://urclhodsgusfdu Nolr Rgrsso So populr
More informationPosition Control of 2-Link SCARA Robot by using Internal Model Control
Mmors of th Faculty of Er, Okayama Uvrsty, Vol, pp 9-, Jauary 9 Posto Cotrol of -Lk SCARA Robot by us Itral Modl Cotrol Shya AKAMASU Dvso of Elctroc ad Iformato Systm Er Graduat School of Natural Scc ad
More information828.^ 2 F r, Br n, nd t h. n, v n lth h th n l nd h d n r d t n v l l n th f v r x t p th l ft. n ll n n n f lt ll th t p n nt r f d pp nt nt nd, th t
2Â F b. Th h ph rd l nd r. l X. TH H PH RD L ND R. L X. F r, Br n, nd t h. B th ttr h ph rd. n th l f p t r l l nd, t t d t, n n t n, nt r rl r th n th n r l t f th f th th r l, nd d r b t t f nn r r pr
More informationDensity estimation II
CS 750 Mche Lerg Lecture 6 esty estmto II Mlos Husrecht mlos@tt.edu 539 Seott Squre t: esty estmto {.. } vector of ttrute vlues Ojectve: estmte the model of the uderlyg rolty dstruto over vrles X X usg
More information46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l pp n nt n th
n r t d n 20 0 : T P bl D n, l d t z d http:.h th tr t. r pd l 46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l
More information