A note on Kumaraswamy Fréchet distribution

Size: px
Start display at page:

Download "A note on Kumaraswamy Fréchet distribution"

Transcription

1 AENSI Jourls Austrl Jourl of Bsc d Appld Sccs ISSN: 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 Sccs Zgzg Egypt A R T I C L E I N F O Artcl hstory: Rcvd 25 Ju 204 Rcvd rvsd form 8 July 204 Accptd 25 August 204 Avll ol 4 Octor 204 Kywords: Kumrswmy Frécht dstruto Epottd Frécht dstruto Mmum llhood stmto A B S T R A C T Th modlg d lyss of lftms s mportt spct of sttstcl wor wd vrty of sctfc d tchologcl flds For th frst tm th clld Kumrswmy Frécht dstruto troducd d studd Th dstruto hs umr of w d wll-ow lftm spcl su-modls For ths modl som of ts sttstcl proprts r studd Th mthod of mmum llhood s usd for stmtg th modl prmtrs d th osrvd formto mtr s drvd Two pplctos to rl dt sts r gv to llustrt th pottlty of ths dstruto 204 AENSI Pulshr All rghts rsrvd ToCt ThsArtcl:Md ME d Ad-Eltw AR A ot o Kumrswmy Frécht Dstruto Aust J Bsc & Appl Sc 8(5): INTRODUCTION Th Frécht dstruto hs pplctos rgg from cclrtd lf tstg through to rthqus floods hors rcg rfll quus suprmrts s currts wd spds d trc rc rcords Th oo of Kotz d Ndrh (2000) dmostrts th pplclty of th Frécht dstruto svrl flds Cordro d d Cstro (200) troducd th Kumrswmy-grtd fmly of dstrutos Th cumultv dstru- to fucto (cdf) of th Kumrswmy grlzd dstrutos (KG) s gv y F G () Th prolty dsty fucto (pdf) corrspodg to () ts th form f g G G (2) Svrl grlzd dstrutos from (2) hv dfd d vstgtd th ltrtur cludg th Kumrswmy Wull dstruto y Cordro t l(200) th Kumrswmy grlzd gmm dstruto y d Cstro t l (20) d th Kumrswmy grlzd hlf-orml dstruto y Cordro t l (202) I ths ppr w propos th Kumrswmy Frécht (KF) dstruto whch tds th Frécht (F) d th pottd Frécht (EF) dstrutos th sm st-up Cordro d d Cstro (200) wth th hop tht t wll ttrct wdr pplcto coomcs ddtolly s svrl rs of study 2 Th Kumrswmy Frécht dstruto: Th cdf d pdf of th Frécht dstruto r rspctvly - G( ; ) 0 0 (3) d - g( ; ) 0 0 (4) Th cdf of th KF dstruto c dfd y susttutg G ( ; ) to quto () Hc t wll ( ) ( ; ) F (5) d th corrspodg pdf s dfd s Corrspodg Author: Md ME Dprtmt of Sttstcs Fculty of Commrc Zgzg Uvrsty Egypt

2 295 Md ME d Ad-Eltw AR f ( ; ) 0 0 (6) whr s scl prmtr d th othr prmtrs d r shp prmtrs Plots of th KF for slctd prmtr vlus 08 & 5 d dffrt vlus of d r gv Fgur =8 =22 =2=22 =5 =2 =2 =05 =08= Fg : Som possl shps of th KF dsty fucto Th survvl fucto S() hzrd rt fucto h() rvrsd hzrd rt fucto r() d th cumultv hzrd rt fucto H() of KF r gv y S( ) F( ) ( ) f( ) - h( ) ( ) S( ) - - f( ) r ( ) F ( ) ( ) d H( ) S( ) ( ) Plots of th HRF for slctd prmtr vlus & 6 d dffrt vlus of r gv Fgur =05 =008 =5 =009 =20 =25 =2 =3 =67= Fg 2: Som possl shps of th HRF 3 Som Spcl Css Not tht th KF dstruto hs svrl wll ow modls s spcl css whch m t of dstgushl sctfc mportc from othr dstrutos - If w t quto (6) rducs to th pottd Frécht (EF) dstruto prstd y Ndrh d Kotz (2003) 2- Sttg w ot th Frécht dstruto 3- If 2 th dsty (6) corrspods to th Kumrswmy vrs Rylgh (KIR) dstruto 4- If 2 d quto (6) coms th pottd vrs Rylgh (EIR) dstruto 5- For th cs 2 d th dsty (6) gvs th vrs Rylgh (IR) dstruto 6- Sttg quto (6) ylds th Kumrswmy vrs potl (KIE) dstruto

3 296 Md ME d Ad-Eltw AR If w gt th pottd vrs potl (EIE) dstruto 8- Wh th pdf (6) rducs to th vrs potl (IE) dstruto 9- Sttg p th dsty (6) coms th Kumrswmy Guml typ-2 (KGuII) dstruto (Shhz t l 202) 0- Gusmáo t l (20) troducd thr prmtrs lftm dstruto co-clld th grlzd vrs Wull dstruto to td som wll-ow dstrutos th lftm ltrtur Thy cocludd tht thr w dstruto s much mor fll th th vrs Wull dstruto d could hv crsg dcrsg d umodl hzrd rts whch r qut rllty d ologcl studs For qc w gt th Kumrswmy grlzd vrs Wull (KGIW) dstruto whch s th tso of grlzd vrs Wull dstruto dfd y Gusmáo t l (20) wth pdf - c q - c q f ( ; c ) c q 0 c 0 (7) For th cs quto (7) ylds th pottd grlzd vrs Wull (EGIW) dstruto ddto to t rducs to grlzd vrs Wull dstruto Tl provds som spcl su-modls of th KF dstruto 4 Epsos for th cumultv d dsty fuctos d sttstcl proprts: Hr w provd smpl psos for th cdf of th KF dstruto dpdg o whthr th prmtr (or ) s rl o-tgr or tgr W cosdr th srs pso ( ) ( ) z z (8) 0! ( ) vld for z < d 0 rl d o-tgr Applcto of (8) to (5) f s rl o-tgr gvs ( ) ( ) F ( ; ) (9) 0! ( ) Ag usg quto (6) w ot ( ) F( ; ) d! ( ) y ( ) dy! ( ) ( ) 0! ( ) J For tgr th sum (9) smply stops t Ag usg (8) w c rwrt (6) s ( ) f ( ; ) 0! ( )( ) whr 0 g ; 0 ( )! ( )( ) d g ; dots th Frécht dsty fucto wth shp prmtr d scl prmtr s tgr th sum (0) s ft d stops t ( ) If 0 Now w dscuss som sttstcl proprts of th KF dstruto (0) -Th mod: Th mod m m m m for KF dstruto s gv y th soluto of ()

4 297 Md ME d Ad-Eltw AR 204 -Th qurtl: p Th qurtl of ordr p for th KF dstruto s gv y th soluto of p ( ) ( p) (2) spcl qurtls my otd y (2) for mpl f p 2 th md s gv -Th momt: As wth y othr dstruto my of th trstg chrctrstcs d fturs of th KF dstruto th c studd through th momts W ot mmdtly th r momt of th KF dstruto Usg th quto (0) th r momt out zro c otd s r r E( ) g ; d 0 0 Bsd o th trsformto y ov prsso d smplfyg th rth momt of KF f r r s r r r E( ) r r (3) 0 Th m vrc Swss d Kurtoss c otd from (3) If 0 s tgr d r th sum stops t If d r quto (3) gvs th rth momt of th EF dstruto wth prmtrs d dstruto -Momt grtg fucto: Now w c drv th momt grtg fucto of th KF dstruto Rcll tht (y Tylor's srs t pso of out zro) t t 0! so th momt-grtg fucto (MGF) of th KF dstruto s gv y t t ( t) E( ) f ( ) d 0 t ( ) d - 0! 0 0! ( ) t ( ) d!! ( ) Bsd o th trsformto y w gt t t ( ) ( ) ( t) E( ) 0 0!! ( ) ( ) 5 Estmto d Fshr formto mtr: Th mmum llhood stmto (MLE) s o of th most wdly usd stmto mthod for fdg th uow prmtrs Lt 2 dpdt rdom smpl from KF Th totl logllhood s gv y ( ) ( ) ( ) ( ) ( ) ( ) ( Z ) ( ) ( W ) whr Z ( ) Z ( ) D d W D Th scor vctor hs compots (4)

5 298 Md ME d Ad-Eltw AR 204 Z Z D W ( ) ( ) W ( ) ( ) ( ) Z ( Z ) ( ) D Z W ( Z ) d ( ) Z Z D W Th mmum llhood stmts (MLEs) of th uow four prmtrs c otd y solvg th systm of olr qutos 0 trtvly For trvl stmto d hypothss tsts o th modl prmtrs w rqur th osrvd formto mtr J J J J J J J J ( ) J J J whos lmts r 2 2 ( ) Z 2 DW Z DW ( ) ( ) ( ) Z DW ( Z ) Z ( DW ) Z ( Z ) Z DW Z DW Z 2 Z DW ( Z ) Z DW 2 2 ( ) ( ) ( ) ( ) 2 Z Z D Z W Z Z D W ( W ) ( D Z W Z Z Z D W W Z Z ( ) Z ( ) 2 2 D W Z D W ( W ) Z 2 ( ) ( ) ( ) ( ) 6 Applcto mpls: To llustrt th w rsults prstd ths ppr w ft th KF dstruto to two mpls of rl dt Th frst mpl s ucsord dt st from Nchols d Pdgtt (2006) cosstg of 00 osrvtos o rg strss of cro frs ( G) Th dt r s follows : Th scod dt st s otd from Smth d Nylor (987) Th dt r th strgths of 5 cm glss frs msurd t th Ntol Physcl Lortory Egld Ufortutly th uts of msurmt r ot gv th ppr Th dt r s follows:

6 299 Md ME d Ad-Eltw AR Ths dt wr prvously studd y Souz t l (20) for t Frécht (BF) pottd Frécht (EF) d Frécht dstrutos I th followg w shll compr th proposd KF dstruto (d thr sumodls KIR KIE EF d F dstrutos ) wth svrl othr thr- d four-prmtr lftm dstrutos mly: th Zogrfos-Blrsh log-logstc (ZBLL) (Zogrfos d Blrsh 2009) th t Frécht (BF) (Ndrh d Gupt 2004 d Souz t l 20) d rctly th Kumrswmy Prto (KP) ( Bourgugo t l 203) modls wth corrspodg dsts: 2 ZBLL : fzbll ( ; ) ( ) ( ) 0 ( ) 0 B( ) ( ) ( ) ( ) BF : fbf ( ; ) ( ) KP : fkp( ; ) ( ) ( ) whr 0 Tl 2 lsts th MLEs of th modl prmtrs for KF KIR KIE BF KP ZBLL EF d F dstrutos th corrspodg stdrd rrors (gv prthss) d th sttstcs ( ˆ ) (whr ( ˆ ) dots th logllhood fucto vlutd t th mmum llhood stmts) A formto crtro (AIC) th Bys formto crtro (BIC) d H-Qu formto crtro (HQIC) Sc th KF dstruto hs th lowst ( ˆ ) AIC BIC d HQIC vlus mog ll th othr modls d so t could chos s th st modl Addtolly t s vdt tht th KIR dstruto prsts th worst ft to th frst dt Smlrly th rsults gv Tl 3 llustrt tht th KF d F dstrutos r th st d th worst modls rspctvly ccordg to th scod dt Th rqurd umrcl vlutos r mplmtd usg th MATHCAD PROGRAM Tl : Som spcl su-modls of th KF dstruto dstruto 2 Kumrswmy vrs Rylgh Kumrswmy vrs potl Epottd Frécht (Ndrh d Kotz2003) 2 Epottd vrs Rylgh Epottd vrs potl Frécht 2 Ivrs Rylgh Ivrs potl p Kumrswmy Guml typ-2(kguii) dstruto (Shhz t l 202) qc Grlzd vrs Wull (Flp t l20) qc Kumrswmy grlzd vrs Wull qc Epottd grlzd vrs Wull Tl 2: MLEs (stdrd rrors prthss) d th sttstcs ( ˆ ) AIC BIC d HQIC; frst dt st Modl KF( ) (2393) KIR( ) (3733) KIE( ) (2663) BF( ) (0236) KP( ) (0502) ZBLL( ) (004) EF( ) (3954) F( ) 8956 (02) (6863) 3974 (064) (2077) (3552) (49552) (00093) (4666) (04) Estmts ( ˆ ) Sttstcs AIC BIC HQIC (2259) (0028) (902) (3006) (252) (09) (0045) (0288) (00897)

7 300 Md ME d Ad-Eltw AR 204 Tl 3: MLEs (stdrd rrors prthss) d th sttstcs ( ) AIC BIC d HQIC; scod dt st Modl KF( ) (7982) KIR( ) (905) KIE( ) 2699 (33675) BF( ) (85) KP( ) (0524) ZBLL( ) 6444 (032) EF( ) (663) F( ) (0059) Estmts (53948) (632) (3473) (8238) (92579) (00039) (2945) (0234) ˆ ( ˆ ) Sttstcs AIC BIC HQIC 2623 (4555) (007) (2955) (37523) (085) (08) (0083) (0632) (036) Cocluso: I fct th KF dstruto rprsts grlzto of som dstrutos prvously cosdrd th ltrtur such s th KGIW KIR KIE EF (Ndrh d Kotz 2003) d Frécht dstrutos Som of ts mthmtcl d sttstcl proprts r studd Prmtr stmto s pprochd y mmum llhood d th osrvd formto mtr s drvd Two umrcl mpls llustrt tht th KF dstruto provds ttr fts th thr su-modls (KIR KIE EF d F dstrutos) d th th othr modls slctd from th ltrtur W hop tht th proposd tdd modl my ttrct wdr pplctos survvl lyss REFERENCES Bourgugo M RB Slv LM Z d GM Cordro 203 Th Kumrswmy Prto dstruto J of Stt Thory d Applctos 2: Cordro GM d M d Cstro 200 A w fmly of grlzd dstrutos Jourl of Sttstcl Computto d Smulto 8: Cordro GM EMMOrtg d S Ndrh 200 Th Kumrswmy Wull dstruto wth pplcto to flur dt J Frl Ist 347: Cordro GM R Pscm d EMM Ortg 202 Th Kumrswmy grlzd hlf- orml dstruto for swd postv dt J Dt Sc 0: Cstro MAR EMM Ortg d GM Cordro 20 Th Kumrswmy grlzd gmm dstruto wth pplcto survvl lyss Stt Mthodol 8: Gusmáo FR EM Ortg d GM Cordro 20 Th grlzd vrs Wull dstruto Sttstcl Pprs Kotz S d S Ndrh 2000 Etrm vlu dstrutos: Thory d pplctos Imprl Collg Prss Ndrh S d AK Gupt 2004 Th t Frécht dstruto Fr Est Jourl of Thortcl Sttstcs 4: 5-24 Ndrh S d S Kotz 2003 Th pottd Frécht dstruto Avll t Itrstt sttourls t Nchols MD d W J Pdgtt 2006 A ootstrp cotrol chrt for Wull Prctls Qulty d Rllty Egrg Itrtol 22: 4-5 Smth RL d JC Nylor 987 A comprso of mmum llhood d Bys stmtors for th thr-prmtr Wull dstruto Appld Sttstcs 36: Shhz MQ S Shhz d NS Butt 202 Th Kumrswmy vrs Wull dstruto Pst Jourl of Sttstcs d Oprto Rsrch 8: Souz WM GM Cordro d AB Sms 20 Som rsults for t Frécht dstruto Commu Sttst Thory-Mth 40: Zogrfos K d N Blrsh 2009 O fmls of t- d grlzd gmm-grtd dstrutos d ssoctd frc Stt Mthod 6:

Statistical properties and applications of a Weibull- Kumaraswamy distribution

Statistical 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 information

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**

ERDOS-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 information

Ekpenyong Emmanuel John and Gideon Sunday N. x (2.1) International Journal of Statistics and Applied Mathematics 2018; 3(4): 60-64

Ekpenyong Emmanuel John and Gideon Sunday N. x (2.1) International Journal of Statistics and Applied Mathematics 2018; 3(4): 60-64 Itrtol Jourl of Sttstcs d Appld Mtmtcs 8; 34 6-64 ISSN 456-45 Mts 8; 34 6-64 8 Stts & Mts www.mtsjourl.com Rcvd 8-5-8 Accptd 9-6-8 Ekpyo Emmul Jo Dprtmt of Sttstcs Mcl Okpr Uvrsty of Arcultur Umudk Nr

More information

THE EXPONENTIATED GENERALIZED FLEXIBLE WEIBULL EXTENSION DISTRIBUTION

THE 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 information

More Statistics tutorial at 1. Introduction to mathematical Statistics

More 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 information

THE TRANSMUTED GENERALIZED PARETO DISTRIBUTION. STATISTICAL INFERENCE AND SIMULATION RESULTS

THE 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 information

3.4 Properties of the Stress Tensor

3.4 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 information

Section 5.1/5.2: Areas and Distances the Definite Integral

Section 5.1/5.2: Areas and Distances the Definite Integral Scto./.: Ars d Dstcs th Dt Itgrl Sgm Notto Prctc HW rom Stwrt Ttook ot to hd p. #,, 9 p. 6 #,, 9- odd, - odd Th sum o trms,,, s wrtt s, whr th d o summto Empl : Fd th sum. Soluto: Th Dt Itgrl Suppos w

More information

SYSTEMS OF LINEAR EQUATIONS

SYSTEMS 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 information

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem Avll t http:pvu.u Appl. Appl. Mth. ISSN: 9-9466 Vol. 0 Issu Dr 05 pp. 007-08 Appltos Appl Mthts: A Itrtol Jourl AAM Etso oruls of Lurll s utos Appltos of Do s Suto Thor Ah Al Atsh Dprtt of Mthts A Uvrst

More information

CBSE , 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 , 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 information

Odd Generalized Exponential Flexible Weibull Extension Distribution

Odd 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 information

TOTAL LEAST SQUARES ALGORITHMS FOR FITTING 3D STRAIGHT LINES

TOTAL 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 information

Unbalanced Panel Data Models

Unbalanced 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 information

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find BSE SMLE ER SOLUTONS LSS-X MTHS SET- BSE SETON Gv tht d W d to fd 7 7 Hc, 7 7 7 Lt, W ow tht Thus, osd th vcto quto of th pl z - + z = - + z = Thus th ts quto of th pl s - + z = Lt d th dstc tw th pot,,

More information

JOURNAL OF COLLEGE OF EDUCATION NO

JOURNAL 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 information

Accuracy of ADC dynamic parameters measurement. Jiri Brossmann, Petr Cesak, Jaroslav Roztocil

Accuracy 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 information

Exponentiated Weibull-Exponential Distribution with Applications

Exponentiated 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 information

Reliability of time dependent stress-strength system for various distributions

Reliability 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 information

CHAPTER 4. FREQUENCY ESTIMATION AND TRACKING

CHAPTER 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 information

Outline. Outline. Outline. Questions. Multivariate Normal Distribution. Multivariate Normal Distribution

Outline. 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 information

On the Beta Mekaham Distribution and Its Applications. Chukwu A. U., Ogunde A. A. *

On the Beta Mekaham Distribution and Its Applications. Chukwu A. U., Ogunde A. A. * Amrca Joural of Mathmatcs ad Statstcs 25, 5(3: 37-43 DOI:.5923/j.ajms.2553.5 O th Bta Mkaham Dstruto ad Its Applcatos Chukwu A. U., Ogud A. A. * Dpartmt of Statstcs, Uvrsty Of Iada, Dpartmt of Mathmatcs

More information

A Monotone Process Replacement Model for a Two Unit Cold Standby Repairable System

A 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 information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 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 information

Linear Prediction Analysis of

Linear 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 information

Outline. Outline. Outline. Questions 2010/9/30. Introduction The Multivariate Normal Density and Its Properties

Outline. 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 information

Bayesian Shrinkage Estimator for the Scale Parameter of Exponential Distribution under Improper Prior Distribution

Bayesian 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 information

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES DEFINITION OF A COMPLEX NUMBER: A umbr of th form, whr = (, ad & ar ral umbrs s calld a compl umbr Th ral umbr, s calld ral part of whl s calld

More information

CHAPTER 7. X and 2 = X

CHAPTER 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 information

Numerical Method: Finite difference scheme

Numerical Method: Finite difference scheme Numrcal Mthod: Ft dffrc schm Taylor s srs f(x 3 f(x f '(x f ''(x f '''(x...(1! 3! f(x 3 f(x f '(x f ''(x f '''(x...(! 3! whr > 0 from (1, f(x f(x f '(x R Droppg R, f(x f(x f '(x Forward dffrcg O ( x from

More information

Introduction to Laplace Transforms October 25, 2017

Introduction 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 information

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of Do Bgyoko () FOURIER SERIES I. INTRODUCTION Srs psos r ubqutous too o scc d grg. Th kds o pso to utz dpd o () th proprts o th uctos to b studd d (b) th proprts or chrctrstcs o th systm udr vstgto. Powr

More information

Linear Prediction Analysis of Speech Sounds

Linear 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 information

Introduction to logistic regression

Introduction to logistic regression Itroducto to logstc rgrsso Gv: datast D { 2 2... } whr s a k-dmsoal vctor of ral-valud faturs or attrbuts ad s a bar class labl or targt. hus w ca sa that R k ad {0 }. For ampl f k 4 a datast of 3 data

More information

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are Itratoal Joural Of Computatoal Egrg Rsarch (crol.com) Vol. Issu. 5 Total Prm Graph M.Rav (a) Ramasubramaa 1, R.Kala 1 Dpt.of Mathmatcs, Sr Shakth Isttut of Egrg & Tchology, Combator 641 06. Dpt. of Mathmatcs,

More information

Handout 7. Properties of Bloch States and Electron Statistics in Energy Bands

Handout 7. Properties of Bloch States and Electron Statistics in Energy Bands Hdout 7 Popts of Bloch Stts d Elcto Sttstcs Eg Bds I ths lctu ou wll l: Popts of Bloch fuctos Podc boud codtos fo Bloch fuctos Dst of stts -spc Elcto occupto sttstcs g bds ECE 407 Spg 009 Fh R Coll Uvst

More information

The Kumaraswamy-Generalized Exponentiated Pareto Distribution

The Kumaraswamy-Generalized Exponentiated Pareto Distribution Europe ourl of Appled Sceces 5 (3): 9-99, 013 ISSN 079-077 IDOSI Pulctos, 013 DOI: 10.589/dos.ejs.013.5.3.1117 The Kumrswmy-Geerled Expoetted Preto Dstruto Trek M. Shms Deprtmet of Sttstcs, Fculty of Commerce,

More information

Independent Domination in Line Graphs

Independent Domination in Line Graphs Itratoal Joural of Sctfc & Egrg Rsarch Volum 3 Issu 6 Ju-1 1 ISSN 9-5518 Iddt Domato L Grahs M H Muddbhal ad D Basavarajaa Abstract - For ay grah G th l grah L G H s th trscto grah Thus th vrtcs of LG

More information

Linear Algebra Existence of the determinant. Expansion according to a row.

Linear 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 information

1. Stefan-Boltzmann law states that the power emitted per unit area of the surface of a black

1. 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 information

minimize c'x subject to subject to subject to

minimize c'x subject to subject to subject to z ' sut to ' M ' M N uostrd N z ' sut to ' z ' sut to ' sl vrls vtor of : vrls surplus vtor of : uostrd s s s s s s z sut to whr : ut ost of :out of : out of ( ' gr of h food ( utrt : rqurt for h utrt

More information

Lecture 1: Empirical economic relations

Lecture 1: Empirical economic relations Ecoomcs 53 Lctur : Emprcal coomc rlatos What s coomtrcs? Ecoomtrcs s masurmt of coomc rlatos. W d to kow What s a coomc rlato? How do w masur such a rlato? Dfto: A coomc rlato s a rlato btw coomc varabls.

More information

Suzan Mahmoud Mohammed Faculty of science, Helwan University

Suzan 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 information

Tolerance Interval for Exponentiated Exponential Distribution Based on Grouped Data

Tolerance Interval for Exponentiated Exponential Distribution Based on Grouped Data Itratoal Rfrd Joural of Egrg ad Scc (IRJES) ISSN (Ol) 319-183X, (Prt) 319-181 Volum, Issu 10 (Octobr 013), PP. 6-30 Tolrac Itrval for Expotatd Expotal Dstrbuto Basd o Groupd Data C. S. Kaad 1, D. T. Shr

More information

Inner Product Spaces INNER PRODUCTS

Inner Product Spaces INNER PRODUCTS MA4Hcdoc Ir Product Spcs INNER PRODCS Dto A r product o vctor spc V s ucto tht ssgs ubr spc V such wy tht th ollowg xos holds: P : w s rl ubr P : P : P 4 : P 5 : v, w = w, v v + w, u = u + w, u rv, w =

More information

Density estimation II

Density 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 information

Major: All Engineering Majors. Authors: Autar Kaw, Luke Snyder

Major: 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 information

Quantum Circuits. School on Quantum Day 1, Lesson 5 16:00-17:00, March 22, 2005 Eisuke Abe

Quantum Circuits. School on Quantum Day 1, Lesson 5 16:00-17:00, March 22, 2005 Eisuke Abe Qutum Crcuts School o Qutum Computg @Ygm D, Lsso 5 6:-7:, Mrch, 5 Esuk Ab Dprtmt of Appl Phscs Phsco-Iformtcs, CEST-JST, Ko vrst Outl Bloch sphr rprstto otto gts vrslt proof A rbtrr cotroll- gt c b mplmt

More information

Order Statistics from Exponentiated Gamma. Distribution and Associated Inference

Order Statistics from Exponentiated Gamma. Distribution and Associated Inference It J otm Mth Scc Vo 4 9 o 7-9 Od Stttc fom Eottd Gmm Dtto d Aoctd Ifc A I Shw * d R A Bo G og of Edcto PO Bo 369 Jddh 438 Sd A G og of Edcto Dtmt of mthmtc PO Bo 469 Jddh 49 Sd A Atct Od tttc fom ottd

More information

1- I. M. ALGHROUZ: A New Approach To Fractional Derivatives, J. AOU, V. 10, (2007), pp

1- I. M. ALGHROUZ: A New Approach To Fractional Derivatives, J. AOU, V. 10, (2007), pp Jourl o Al-Qus Op Uvrsy or Rsrch Sus - No.4 - Ocobr 8 Rrcs: - I. M. ALGHROUZ: A Nw Approch To Frcol Drvvs, J. AOU, V., 7, pp. 4-47 - K.S. Mllr: Drvvs o or orr: Mh M., V 68, 995 pp. 83-9. 3- I. PODLUBNY:

More information

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since 56 Chag Ma J Sc 0; () Chag Ma J Sc 0; () : 56-6 http://pgscccmuacth/joural/ Cotrbutd Papr Th Padova Sucs Ft Groups Sat Taș* ad Erdal Karaduma Dpartmt of Mathmatcs, Faculty of Scc, Atatürk Uvrsty, 50 Erzurum,

More information

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data

On 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 information

Aotomorphic Functions And Fermat s Last Theorem(4)

Aotomorphic Functions And Fermat s Last Theorem(4) otomorphc Fuctos d Frmat s Last Thorm(4) Chu-Xua Jag P. O. Box 94 Bg 00854 P. R. Cha agchuxua@sohu.com bsract 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

Second Handout: The Measurement of Income Inequality: Basic Concepts

Second 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 information

A Class of Harmonic Meromorphic Functions of Complex Order

A 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 information

IFYFM002 Further Maths Appendix C Formula Booklet

IFYFM002 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 information

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP)

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP) th Topc Compl Nmbrs Hyprbolc fctos ad Ivrs hyprbolc fctos, Rlato btw hyprbolc ad crclar fctos, Formla of hyprbolc fctos, Ivrs hyprbolc fctos Prpard by: Prof Sl Dpartmt of Mathmatcs NIT Hamrpr (HP) Hyprbolc

More information

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit

Binary 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 information

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space.

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space. Rpatd Trals: As w hav lood at t, th thory of probablty dals wth outcoms of sgl xprmts. I th applcatos o s usually trstd two or mor xprmts or rpatd prformac or th sam xprmt. I ordr to aalyz such problms

More information

Different types of Domination in Intuitionistic Fuzzy Graph

Different types of Domination in Intuitionistic Fuzzy Graph Aals of Pur ad Appld Mathmatcs Vol, No, 07, 87-0 ISSN: 79-087X P, 79-0888ol Publshd o July 07 wwwrsarchmathscorg DOI: http://dxdoorg/057/apama Aals of Dffrt typs of Domato Itutostc Fuzzy Graph MGaruambga,

More information

NHPP and S-Shaped Models for Testing the Software Failure Process

NHPP 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 information

The Beta Inverted Exponential Distribution: Properties and Applications

The Beta Inverted Exponential Distribution: Properties and Applications Volum, Issu 5, ISSN (Ol): 394-894 Th Bta Ivrtd Epotal Dstrbuto: Proprts ad Applcatos Bhupdra Sgh Dpartmt of Statstcs, Ch. Chara Sgh Uvrsty, Mrut, Ida Emal: bhupdra.raa@gmal.com Rtu Gol Dpartmt of Statstcs,

More information

Ch 1.2: Solutions of Some Differential Equations

Ch 1.2: Solutions of Some Differential Equations Ch 1.2: Solutions of Som Diffrntil Equtions Rcll th fr fll nd owl/mic diffrntil qutions: v 9.8.2v, p.5 p 45 Ths qutions hv th gnrl form y' = y - b W cn us mthods of clculus to solv diffrntil qutions of

More information

SAMPLE LITANY OF THE SAINTS E/G. Dadd9/F. Aadd9. cy. Christ, have. Lord, have mer cy. Christ, have A/E. Dadd9. Aadd9/C Bm E. 1. Ma ry and. mer cy.

SAMPLE LITANY OF THE SAINTS E/G. Dadd9/F. Aadd9. cy. Christ, have. Lord, have mer cy. Christ, have A/E. Dadd9. Aadd9/C Bm E. 1. Ma ry and. mer cy. LTNY OF TH SNTS Cntrs Gnt flwng ( = c. 100) /G Ddd9/F ll Kybrd / hv Ddd9 hv hv Txt 1973, CL. ll rghts rsrvd. Usd wth prmssn. Musc: D. Bckr, b. 1953, 1987, D. Bckr. Publshd by OCP. ll rghts rsrvd. SMPL

More information

Two Fluids Viscous Dark Energy Cosmological Models with Linearly. Varying Deceleration Parameter in Self Creation Cosmology

Two Fluids Viscous Dark Energy Cosmological Models with Linearly. Varying Deceleration Parameter in Self Creation Cosmology Prspct Jourl Sptr 0 Volu 5 Issu 9 pp 9-90 hrd, V R, Shkh, S H & Rht, P N, To Fluds Vscous rk Ergy osologcl Modls th Lrly Vryg clrto Prtr Slf rto osology 9 rtcl To Fluds Vscous rk Ergy osologcl Modls th

More information

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex.

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex. Lnr lgr Vctors gnrl -dmnsonl ctor conssts of lus h cn rrngd s column or row nd cn rl or compl Rcll -dmnsonl ctor cn rprsnt poston, loct, or cclrton Lt & k,, unt ctors long,, & rspctl nd lt k h th componnts

More information

The Analyses and Applications of the Traffic Dispersion Model

The Analyses and Applications of the Traffic Dispersion Model Th Alss d Applctos of th Trffc Dsprso Modl Hsu-Jug Cho d Shh-Chg Lo Dprtmt of TrsporttoTcholog d Mgmt Ntol Cho Tug Uvrst, T Hsuh Rd., HsChu, 49 TAIWAN Abstrct: - I ths stud, w dscuss th drvto, pplctos

More information

Let's revisit conditional probability, where the event M is expressed in terms of the random variable. P Ax x x = =

Let'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 information

Chapter 3 Fourier Series Representation of Periodic Signals

Chapter 3 Fourier Series Representation of Periodic Signals Chptr Fourir Sris Rprsttio of Priodic Sigls If ritrry sigl x(t or x[] is xprssd s lir comitio of som sic sigls th rspos of LI systm coms th sum of th idividul rsposs of thos sic sigls Such sic sigl must:

More information

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis

Department 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 information

A NEW GENERALIZATION OF THE EXPONENTIAL-GEOMETRIC DISTRIBUTION

A NEW GENERALIZATION OF THE EXPONENTIAL-GEOMETRIC DISTRIBUTION Jou of Sttstcs: Advcs Thoy d Actos Voum 7 Num Pgs 5-48 A NW GNRAIZATION OF TH PONNTIA-GOMTRIC DISTRIBUTION M. NASSAR d N. NADA Dtmt of Mthmtcs Fcuty of Scc A Shms Uvsty Ass Co 566 gyt -m: m_ss_999@yhoo.com

More information

Special Curves of 4D Galilean Space

Special 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 information

Exp-Kumaraswamy Distributions: Some Properties and Applications

Exp-Kumaraswamy Distributions: Some Properties and Applications Joul of Sccs, Islmc Rpulc of I 26: 57-69 25 Uvsy of Th, ISSN 6-4 hp://sccs.u.c. Ep-Kumswmy Dsuos: Som Pops d Applcos Z. Jvsh, A. H Rd *, d N.R. Aghm Dpm of Sscs, Fculy of Mhmcl Sccs, Fdows Uvsy of Mshhd,

More information

OPTIMAL STEP-STRESS PLANS FOR ACCELERATED LIFE TESTING CONSIDERING RELIABILITY/LIFE PREDICTION

OPTIMAL 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 information

The Marshall-Olkin-Kumaraswamy-G family of distributions

The Marshall-Olkin-Kumaraswamy-G family of distributions Th Mrshll-Ol-Kumrswmy- mly o dsruos L Hdu d Sur Chrory* Drm o Sscs Drurh Uvrsy Drurh-7864 Id *Corrsod uhor: Eml: sur_ss@dru.c. Auus 6 Asrc A w mly o couous dsruo s roosd y us Kumrswmy- Cordro d d Csro

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

Kummer Beta -Weibull Geometric Distribution. A New Generalization of Beta -Weibull Geometric Distribution

Kummer Beta -Weibull Geometric Distribution. A New Generalization of Beta -Weibull Geometric Distribution ttol Jol of Ss: Bs Al Rsh JSBAR SSN 37-453 Pt & Ol htt://gss.og/.h?joljolofbsaal ---------------------------------------------------------------------------------------------------------------------------

More information

A New Generalization of Quadratic Hazard Rate Distribution

A New Generalization of Quadratic Hazard Rate Distribution A Nw Gnlzton of Qudtc Hzd Rt Dstuton Ihm Eltl Insttut of Sttstcl Studs nd Rsch Dptmnt of Mthmtcl Sttstcs, Co Unvsty _ltl@stff.cu.du.g Ndm Shfqu Butt COMSATS Insttut of Infomton Tchnology, Lho ndmshfqu@ctlho.du.pk

More information

Three-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations

Three-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 information

Stability Analysis of an Electric Parking Brake (EPB) System with a Nonlinear Proportional Controller

Stability Analysis of an Electric Parking Brake (EPB) System with a Nonlinear Proportional Controller Procdgs of th 17th World Cogrss h Itrtol Fdrto of utomtc Cotrol Stblty lyss of Elctrc Prkg Brk (EPB) Systm wth Nolr Proportol Cotrollr Youg O. L *, Choog W. L *, Chug C. Chug **, Yougsup So ***, Pljoo

More information

How much air is required by the people in this lecture theatre during this lecture?

How much air is required by the people in this lecture theatre during this lecture? 3 NTEGRATON tgrtio is us to swr qustios rltig to Ar Volum Totl qutity such s: Wht is th wig r of Boig 747? How much will this yr projct cost? How much wtr os this rsrvoir hol? How much ir is rquir y th

More information

A study of stochastic programming having some continuous random variables

A study of stochastic programming having some continuous random variables Itratoal Joural of Egrg Trds ad Tchology (IJETT) Volu 7 Nur 5 - July 06 A study of stochastc prograg havg so cotuous rado varals Mr.Hr S. Dosh, Dr.Chrag J. Trvd, Assocat Profssor, H Collg of Corc Navragura,

More information

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals

Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals Intgrtion Continud Intgrtion y Prts Solving Dinit Intgrls: Ar Undr Curv Impropr Intgrls Intgrtion y Prts Prticulrly usul whn you r trying to tk th intgrl o som unction tht is th product o n lgric prssion

More information

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1

The 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 information

ON ESTIMATION OF STRESS STRENGTH MODEL FOR GENERALIZED INVERTED EXPONENTIAL DISTRIBUTION

ON ESTIMATION OF STRESS STRENGTH MODEL FOR GENERALIZED INVERTED EXPONENTIAL DISTRIBUTION Joural of Rlablt ad Statstcal Studs; ISSN Prt: 974-84, Ol:9-5666 Vol. 6, Issu 3: 55-63 ON ESTIMATION OF STRESS STRENGTH MODEL FOR GENERALIZED INVERTED EXPONENTIAL DISTRIBUTION Mohad A. Hussa Dpartt of

More information

Handout 11. Energy Bands in Graphene: Tight Binding and the Nearly Free Electron Approach

Handout 11. Energy Bands in Graphene: Tight Binding and the Nearly Free Electron Approach Hdout rg ds Grh: Tght dg d th Nrl Fr ltro roh I ths ltur ou wll lr: rg Th tght bdg thod (otd ) Th -bds grh FZ C 407 Srg 009 Frh R Corll Uvrst Grh d Crbo Notubs: ss Grh s two dsol sgl to lr o rbo tos rrgd

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

Chapter 16. 1) is a particular point on the graph of the function. 1. y, where x y 1

Chapter 16. 1) is a particular point on the graph of the function. 1. y, where x y 1 Prctic qustions W now tht th prmtr p is dirctl rltd to th mplitud; thrfor, w cn find tht p. cos d [ sin ] sin sin Not: Evn though ou might not now how to find th prmtr in prt, it is lws dvisl to procd

More information

page 11 equation (1.2-10c), break the bar over the right side in the middle

page 11 equation (1.2-10c), break the bar over the right side in the middle I. Corrctios Lst Updtd: Ju 00 Complx Vrils with Applictios, 3 rd ditio, A. Dvid Wusch First Pritig. A ook ought for My 007 will proly first pritig With Thks to Christi Hos of Swd pg qutio (.-0c), rk th

More information

(A) the function is an eigenfunction with eigenvalue Physical Chemistry (I) First Quiz

(A) the function is an eigenfunction with eigenvalue Physical Chemistry (I) First Quiz 96- Physcl Chmstry (I) Frst Quz lctron rst mss m 9.9 - klogrm, Plnck constnt h 6.66-4 oul scon Sp of lght c. 8 m/s, lctron volt V.6-9 oul. Th functon F() C[cos()+sn()] s n gnfuncton of /. Th gnvlu s (A)

More information

THE BETA GENERALIZED PARETO DISTRIBUTION

THE BETA GENERALIZED PARETO DISTRIBUTION Jourl of Sttstcs: Advces Theory d Applctos Volue 6 Nuer / Pges -7 THE BETA GENERALIZED PARETO DISTRIBUTION M M NASSAR d N K NADA Deprtet of Mthetcs Fculty of Scece A Shs Uversty Ass Cro 566 Egypt e-l:

More information

On Matrices associated with L-Fuzzy Graphs

On Matrices associated with L-Fuzzy Graphs lol Jorl of Pr d Appld Mthmts ISSN 973-768 olm 3 Nmr 6 7 pp 799-8 Rsrh Id Pltos http://wwwrpltoom O Mtrs ssotd wth -Fzzy rphs Prmd Rmhdr P Dprtmt of Mthmts St Pl s Collg Klmssry Koh-683 53 Krl Id K Thoms

More information

Quantum Mechanics & Spectroscopy Prof. Jason Goodpaster. Problem Set #2 ANSWER KEY (5 questions, 10 points)

Quantum Mechanics & Spectroscopy Prof. Jason Goodpaster. Problem Set #2 ANSWER KEY (5 questions, 10 points) Chm 5 Problm St # ANSWER KEY 5 qustios, poits Qutum Mchics & Spctroscopy Prof. Jso Goodpstr Du ridy, b. 6 S th lst pgs for possibly usful costts, qutios d itgrls. Ths will lso b icludd o our futur ms..

More information

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao

More information

Photon-phonon interaction in photonic crystals

Photon-phonon interaction in photonic crystals IOP Cofr Srs: Mtrls S d Egrg Photo-phoo trto photo rystls To t ths rtl: T Ut IOP Cof. Sr.: Mtr. S. Eg. 3 Vw th rtl ol for updts d hmts. Rltd ott - study o optl proprts of photo rystls osstg of hollow rods

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4.

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4. Coutg th compostos of a postv tgr usg Gratg Fuctos Start wth,... - Whr, for ampl, th co-ff of s, for o summad composto of aml,. To obta umbr of compostos of, w d th co-ff of (...) ( ) ( ) Hr for stac w

More information

MODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f

MODEL 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 information

Efficient Computations for Evaluating Extended Stochastic Petri Nets using Algebraic Operations

Efficient 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 information

Fundamentals of Continuum Mechanics. Seoul National University Graphics & Media Lab

Fundamentals of Continuum Mechanics. Seoul National University Graphics & Media Lab Fndmntls of Contnm Mchncs Sol Ntonl Unvrsty Grphcs & Md Lb Th Rodmp of Contnm Mchncs Strss Trnsformton Strn Trnsformton Strss Tnsor Strn T + T ++ T Strss-Strn Rltonshp Strn Enrgy FEM Formlton Lt s Stdy

More information