The Odd Generalized Exponential Modified. Weibull Distribution

Size: px
Start display at page:

Download "The Odd Generalized Exponential Modified. Weibull Distribution"

Transcription

1 Itatoal Mathmatcal oum Vol. 6 o HIKARI td Th Odd Galzd Epotal Modd Wbull Dstbuto Yassm Y. Abdlall Dpatmt o Mathmatcal Statstcs Isttut o Statstcal Studs ad Rsach Cao Uvsty Egypt Copyght 6 Yassm Y. Abdlall. Ths atcl s dstbutd ud th Catv Commos Attbuto cs whch pmts ustctd us dstbuto ad poducto ay mdum povdd th ogal wo s poply ctd. Abstact I ths pap w popos a w dstbuto calld th odd galzd potal modd Wbull dstbuto. Som mathmatcal popts o th w dstbuto a studd. Th mthod o mamum llhood s usd o stmatg th modl paamts ad th obsvd sh's omato mat s dvd. W llustat th usulss o th poposd modl by applcato to al data. Kywods: Modd Wbull dstbuto momts mamum llhood stmato od statstcs. Itoducto Th modd Wbull MW dstbuto s o o th most mpotat dstbutos ltm modlg ad som wll-ow dstbutos such as th potal Raylgh la alu at ad Wbull dstbutos a spcal cass o t. Ths dstbuto was toducd by a ad Muthy 3 to whch w th ad o a dtald dscusso as wll as applcatos o th MW dstbuto patcula th us o th al data st pstg alu tms to llustat th modlg ad stmato pocdu. Also Saha ad Zad 9 toducd th modd Wbull dstbuto. It ca b usd to dscb sval lablty modls. It has th paamts two scal ad o shap paamts. Rctly Caasco t al. 8 tdd th MW dstbuto by addg aoth shap paamt ad toducg a ou paamt galzd MW GMW ad log-gmw GMW.

2 944 Yassm Y. Abdlall Rctly Tah t al. 5 poposd a w class o uvaat dstbutos calld th odd galzd potal OGE amly ad studd ach o th OGE- Wbull OGE-W dstbuto th OGE-écht OGE- dstbuto ad th OGE-Nomal OGE-N dstbuto. Ths mthod s lbl bcaus th hazad at shaps could b casg dcasg bathtub ad upsd dow bathtub. I ths atcl w pst a w dstbuto om th odd galzd potal dstbuto ad modd Wbull dstbuto calld th Odd Galzd Epotal-Modd Wbull OGE-MW dstbuto usg w amly o uvaat dstbutos poposd by Tah t al. 5. A adom vaabl s sad to hav galzd potal GE dstbuto wth paamts th cumulatv dstbuto ucto cd s gv by. Th Odd Galzd Epotal amly by Tah t al. 5 s dd as ollows. t G s th cd o ay dstbuto dpds o paamt ad thus th suvval ucto s G G th th cd o OGE-amly s G dd by placg CD o GE Equato by to gt G G G. Wh a two addtoal paamts. Ths pap s outld as ollows. I Scto w d th cumulatv dstbuto ucto dsty uctolablty ucto ad hazad ucto o th Odd Galzd Epotal-Modd Wbull OGE-MW dstbuto. I Scto 3 w toduc th statstcal popts clud th quatl ucto th mda adth momts. Scto 4 dscusss th dstbuto o th od statstcs o OGE-MW dstbuto. Moov mamum llhood stmato o th paamts s dtmd Scto 5. ally a applcato o OGE-MW usg a al data st s pstd Scto 6.. Th OGE-MW Dstbuto. OGE-MW spccatos I ths scto w d w v paamts dstbuto calld Odd Galzd Epotal-Modd Wbull dstbuto wth paamts ad wtt as OGE-MWΘ wh th vcto Θ s dd by Θ =.

3 Odd galzd potal modd Wbull dstbuto 945 A adom vaabl s sad to hav OGE-MW wth paamts ad ts cumulatv dstbuto ucto cd gv as ollows. wh a scal paamts ad a shap paamts. Hc th cospodg pobablty dsty ucto pd s. 3. Suvval ad hazad uctos I a adom vaabl has cd th th cospodg suvval ucto s gv by. S Th hazad ucto o OGE-MW s dd as ollow. S h gu ad 3 llustats som o th possbl shaps o th pd cd ad hazad ucto o OGE-MW dstbuto o som valus o th paamts ad

4 946 Yassm Y. Abdlall gu. Th pd s o vaous OGE-MW dstbutos gu.th cd o vaous OGE-MW dstbutos. 4 h t h t h t h t h t t gu 3. Th hazad ucto o vaous OGE-MW dstbutos.

5 Odd galzd potal modd Wbull dstbuto 947 Not that thoge-mw dstbuto s vy lbl modl that appoachs to dt dstbutos wh ts paamts a chagd. Th OGE-MW dstbuto cotas as spcal-modls wth th ollowg wll ow dstbutos. I patcula o w hav th odd galzd potal- Wbull OGE-W dstbuto as dscussd Tah t al. 5. Th odd galzd potal-potaloge-e dstbuto s claly a spcal cas o ad as dscussd Mat ad Pama 5.o / ad w hav th odd galzd potal-la alu at OGE- R dstbuto as dscussd El-Damcs t al. 5. Wh ad th th sultg dstbuto s th odd galzd potal-raylgh OGE-R dstbuto. 3. Statstcal Popts Ths scto s dvotd o studyg somstatstcal popts o th odd galzd potal-modd Wbull OGE-MW spccally quatl mda ad th momts. 3. Quatl ad Mda o OGE-MW Th quatl ucto q o OGE-MWΘ dstbuto s gv by usg q q 4 Substtutg om to 4 q s th al soluto o th ollowg quato q q l q l q Th abov quato has o closd om soluto q so w hav to us a umcal tchqu such as a Nwto- Raphso mthod to gt th quatl. By puttg q. 5 Equato 5 w ca gt th mda o odd galzd potal modd Wbull dstbuto. 3. Momts Momts a cssay ad mpotat ay statstcal aalyss spcally applcatos. It ca b usd tostudy th most mpotat atus ad chaactstcs o a dstbuto.g. tdcy dspso swss ad utoss. I ths subscto w wll dv th th momts o th OGE-MWΘ dstbuto as t ss paso. 5

6 948 Yassm Y. Abdlall Thom. Th th momt o a adom vaabl ~ OGE-MWΘ wh Θ = s gv ' Poo: Th th momt o a adom vaabl wth pd s dd by ' d 6 Substtutg om 3 to 6 w obta. ' d 7 Sc o w obta. 8 Substtutg om 8 to 7 w gt. ' d Usg ss paso o w obta. ' d Usg bomal paso o w obta

7 Odd galzd potal modd Wbull dstbuto 949 '. d Usg ss paso o w obta '. d d By usg th dto o gamma ucto th om s Zwllg 4. z dt t z z t z ally w obta th th momt o OGE-MW as ollows. ' Ths complts th poo. 4. Od Statstcs t... b a smpl adom sampl o sz om OGE-MWΘwth cumulatv dstbuto ucto ad pobablty dsty ucto gv by ad 3 spctvly. t : : :... dot th od statstcs obtad om ths sampl. Th pobablty dsty ucto o : s gv by : B 9

8 95 Yassm Y. Abdlall wh ad a th pd ad cd o OGE-MWΘ dstbuto gv by ad 3 spctvly ad B.. s th bta ucto also w d st od statstcs... m : ad th last od statstcs as... ma :. Sc o w ca us th bomal paso o gv as ollows. Substtutg om to 9 w obta. : B Substtutg om ad 3 to w obta. : Rlato shows that : s th wghtd avag o th odd galzd potal-modd Wbull wth dt shap paamts. 5. Estmato ad Ic Now w dscuss th stmato o th OGE-MW paamts by usg th mthod o mamum llhood basd o a complt sampl. 5. Mamum llhood stmatos t... b a adom sampl o sz om OGE-MWΘ wh Θ = th th llhood ucto l o ths sampl s dd as. l 3 Substtutg om 3 to 3 w gt. l Th log-llhood ucto bcoms:

9 Odd galzd potal modd Wbull dstbuto 95. l l l l 4 Th mamum llhood stmats o th paamts a obtad by Dtatg th log-llhood ucto wth spct to th paamts ad sttg th sult to zo. l l l l l 8 ad l 9 Wh th ola uctos ad a gv by.

10 95 Yassm Y. Abdlall om quato 9 w obta th mamum llhood stmat o a closd om as ollow. l Substtutg om to ad 8 w gt th MEs o by solvg th ollowg systm o o-la quatos l l l l l wh ad. Ths quatos caot b solvd aalytcally ad statstcal sotwa ca b usd to solv th quatos umcally. W ca us tatv tchqus such as Nwto Raphso typ algothm to obta th stmat.

11 Odd galzd potal modd Wbull dstbuto Asymptotc codc bouds I ths subscto w dv th asymptotc codc tvals o th uow paamts ad. As th sampl sz th appoachs a multvaat omal vcto wth zo mas ad aac mat I wh I s th vs o th obsvdomato mat whch dd as ollows I Va Va Va Va Va Th scod patal dvatvs cludd I a gv as ollows

12 954 Yassm Y. Abdlall l

13 Odd galzd potal modd Wbull dstbuto 955 l l l l l l l

14 956 Yassm Y. Abdlall l l l l l l l l l wh ad. Th asymptotc % codc tvals o ad a Va z Va z Va z Va z ad

15 Odd galzd potal modd Wbull dstbuto 957 z Va spctvly wh stadad omal dstbuto. 6. Data Aalyss z s th upp th pctl o th I ths scto w pom a applcato to al data to llustat that th OGE- MW ca b a good ltm modl compag wth may ow dstbutos such as th Epotal E Galzd Epotal GE a alu Rat R ad Wbull W. Cosd th data hav b obtad om Aast [] ad wdly potd may ltatus. It psts th ltms o 5 dvcs ad also possss a bathtub-shapd alu at popty Tabl. Tabl : Th data om Aast [] Th mamum llhood stmats MEs o th uow paamts o th v modls s gv Tabl. Tabl.MEs o th paamts Th Modl E GE R W OGEMW ME o th paamts Th valus o log-llhood uctos - Aa Iomato Cta AIC Baysa Iomato Cta BIC ad th Cosstt Aa Iomato Cta CAIC a gv Tabl 3 o th v modls od to vy whch dstbuto ts btt to ths data.

16 958 Yassm Y. Abdlall Tabl 3.Th - AIC BIC ad CAIC o dvcs data. Th Modl Masus AIC BIC CAIC E GE R W OGE-MW Basd o Tabl ad 3 t s show that OGE-MW modl povd btt t to th data ath tha oth dstbutos whch w compad wth bcaus t has th smallst valu o AIC BIC CAIC. Substtutg th MEs o th uow paamts to w gt stmato o th vaac aac mat as th ollowg: I Th appomat 95% two sdd codc tvals o th uow paamts ad a [.74.78] [.43] [.] [ ] ad [ ] spctvly. 7. Coclusos I ths pap w hav toducd a w v-paamt modl calld odd galzd potal modd Wbull OGE-MW dstbuto ad studd ts dt popts. Som statstcal popts o ths dstbuto hav b dvd ad dscussd. W povd th pd th cd ad th hazad at ucto o th w modl also w povd a plct psso o th momts. Th dstbutos o th od statstcs a dscussd. Both pot ad asymptotc codc tval stmats o th paamts a dvd usg mamum llhood mthod ad w obtad th obsvd sh omato mat. W us applcato o st o al data to compa th OGE-MW wth oth ow dstbutos such as Epotal E Galzd Epotal GE a alu Rat R ad Wbull W. Applcatos o st o al data showd that th OGE-MW s th bst dstbutoo ttg ths data sts compad wth oth dstbutos cosdd ths atcl.

17 Odd galzd potal modd Wbull dstbuto 959 Rcs [] M. V. Aast How to dty a bathtub hazad at IEEE Tasactos o Rlablty o [] J. M. Caasco E. M. Otga ad G. M. Codo A galzato modd wbull dstbuto o ltm modlg Computatoal Statstcs ad Data Aalyss 53 8 o [3] M. A. El-Damcs A. Mustaa B. S. El-Dsouy ad M. E. Mustaa Th odd galzd potal la alu at dstbuto Joual o Statstcs Applcatos & Pobablty [4] C. D. a M. ad D.N.P. Muthy A modd Wbull dstbuto IEEE Tasactos o Rlablty [5] S. S Mat ad S. Pama Odds galzd potal-potal dstbuto Joual o Data Scc [6] A. M. Saha ad M. Zad Modd Wbull dstbuto Appld Sccs [7] M. H. Tah G. M. Codo M. Alzadh M. Masoo M. Zuba ad G. G. Hamda Th odd galzd potal amly o dstbutos wth applcatos Joual o Statstcal Dstbutos ad Applcatos 5 o [8] D. Zwllg Tabl o Itgals Ss ad Poducts Elsv Ic. 4. Rcvd: July 6 Publshd: Octob 3 6

International Journal of Advanced Scientific Research and Management, Volume 3 Issue 11, Nov

International Journal of Advanced Scientific Research and Management, Volume 3 Issue 11, Nov 199 Algothm ad Matlab Pogam fo Softwa Rlablty Gowth Modl Basd o Wbull Od Statstcs Dstbuto Akladswa Svasa Vswaatha 1 ad Saavth Rama 2 1 Mathmatcs, Saaatha Collg of Egg, Tchy, Taml Nadu, Ida Abstact I ths

More information

SIMULTANEOUS METHODS FOR FINDING ALL ZEROS OF A POLYNOMIAL

SIMULTANEOUS METHODS FOR FINDING ALL ZEROS OF A POLYNOMIAL Joual of athmatcal Sccs: Advacs ad Applcatos Volum, 05, ags 5-8 SIULTANEUS ETHDS FR FINDING ALL ZERS F A LYNIAL JUN-SE SNG ollg of dc Yos Uvsty Soul Rpublc of Koa -mal: usopsog@yos.ac. Abstact Th pupos

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

New bounds on Poisson approximation to the distribution of a sum of negative binomial random variables

New bounds on Poisson approximation to the distribution of a sum of negative binomial random variables Sogklaaka J. Sc. Tchol. 4 () 4-48 Ma. -. 8 Ogal tcl Nw bouds o Posso aomato to th dstbuto of a sum of gatv bomal adom vaabls * Kat Taabola Datmt of Mathmatcs Faculty of Scc Buaha Uvsty Muag Chobu 3 Thalad

More information

International Journal of Pure and Applied Sciences and Technology

International Journal of Pure and Applied Sciences and Technology I J Pu Appl Sc Tchol 8 pp 59-7 Iaoal Joual o Pu ad Appld Sccs ad Tchology ISSN 9-67 Avalabl ol a wwwopaasa Rsach Pap Tasmud Quas Ldly Dsbuo: A Galzao o h Quas Ldly Dsbuo I Elbaal ad M Elgahy * Isu o Sascal

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

Edge Product Cordial Labeling of Some Cycle Related Graphs

Edge Product Cordial Labeling of Some Cycle Related Graphs Op Joua o Dsct Mathmatcs, 6, 6, 68-78 http://.scp.o/joua/ojdm ISSN O: 6-7643 ISSN Pt: 6-7635 Ed Poduct Coda Lab o Som Cyc Ratd Gaphs Udaya M. Pajapat, Ntta B. Pat St. Xav s Co, Ahmdabad, Ida Shaksh Vaha

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

Professor Wei Zhu. 1. Sampling from the Normal Population

Professor Wei Zhu. 1. Sampling from the Normal Population AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple

More information

The Exponentiated Lomax Distribution: Different Estimation Methods

The Exponentiated Lomax Distribution: Different Estimation Methods Ameca Joual of Appled Mathematcs ad Statstcs 4 Vol. No. 6 364-368 Avalable ole at http://pubs.scepub.com/ajams//6/ Scece ad Educato Publshg DOI:.69/ajams--6- The Expoetated Lomax Dstbuto: Dffeet Estmato

More information

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r.

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r. Statcs Th cotact btw a mapulato ad ts vomt sults tactv ocs ad momts at th mapulato/vomt tac. Statcs ams at aalyzg th latoshp btw th actuato dv tous ad th sultat oc ad momt appld at th mapulato dpot wh

More information

Development of indirect EFBEM for radiating noise analysis including underwater problems

Development of indirect EFBEM for radiating noise analysis including underwater problems csnk 03 It. J. Naval cht. Oca E. 03 5:39~403 http://dx.do.o/0.478/ijnoe-03-04 Dvlopmt of dct EFBEM fo adat os aalyss clud udwat poblms Hyu-Wu Kwo Su-Yoo Ho ad J-Hu So 3 Rsach Isttut of Ma Systms E RIMSE

More information

Chapter 2 Reciprocal Lattice. An important concept for analyzing periodic structures

Chapter 2 Reciprocal Lattice. An important concept for analyzing periodic structures Chpt Rcpocl Lttc A mpott cocpt o lyzg podc stuctus Rsos o toducg cpocl lttc Thoy o cystl dcto o x-ys, utos, d lctos. Wh th dcto mxmum? Wht s th tsty? Abstct study o uctos wth th podcty o Bvs lttc Fou tsomto.

More information

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof MATEC Web of Cofeeces ICIEA 06 600 (06) DOI: 0.05/mateccof/0668600 The ea Pobablty Desty Fucto of Cotuous Radom Vaables the Real Numbe Feld ad Its Estece Poof Yya Che ad Ye Collee of Softwae, Taj Uvesty,

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

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

Homework 1: Solutions

Homework 1: Solutions Howo : Solutos No-a Fals supposto tst but passs scal tst lthouh -f th ta as slowss [S /V] vs t th appaac of laty alty th path alo whch slowss s to b tat to obta tavl ts ps o th ol paat S o V as a cosquc

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

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

2.1.1 The Art of Estimation Examples of Estimators Properties of Estimators Deriving Estimators Interval Estimators

2.1.1 The Art of Estimation Examples of Estimators Properties of Estimators Deriving Estimators Interval Estimators . ploatoy Statstcs. Itoducto to stmato.. The At of stmato.. amples of stmatos..3 Popetes of stmatos..4 Devg stmatos..5 Iteval stmatos . Itoducto to stmato Samplg - The samplg eecse ca be epeseted by a

More information

Today s topics. How did we solve the H atom problem? CMF Office Hours

Today s topics. How did we solve the H atom problem? CMF Office Hours CMF Offc ous Wd. Nov. 4 oo-p Mo. Nov. 9 oo-p Mo. Nov. 6-3p Wd. Nov. 8 :30-3:30 p Wd. Dc. 5 oo-p F. Dc. 7 4:30-5:30 Mo. Dc. 0 oo-p Wd. Dc. 4:30-5:30 p ouly xa o Th. Dc. 3 Today s topcs Bf vw of slctd sults

More information

Transmuted Exponentiated Gamma Distribution: A Generalization of the Exponentiated. Gamma Probability Distribution

Transmuted Exponentiated Gamma Distribution: A Generalization of the Exponentiated. Gamma Probability Distribution Appld Mathatcal Sccs Vol. 8 04 o. 7 97-30 HIKARI Ltd www.-hkar.co http//d.do.org/0.988/as.04.405 Trasutd Epotatd Gaa Dstrbuto A Gralzato o th Epotatd Gaa Probablty Dstrbuto Mohad A. Hussa Dpartt o Mathatcal

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

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

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

SOME IMPUTATION METHODS IN DOUBLE SAMPLING SCHEME FOR ESTIMATION OF POPULATION MEAN

SOME IMPUTATION METHODS IN DOUBLE SAMPLING SCHEME FOR ESTIMATION OF POPULATION MEAN aoal Joual of Mod Egg Rsach (JMER) www.jm.com ol. ssu. Ja-F 0 pp-00-07 N: 9- OME MPUTATON METHOD N DOUBLE AMPLNG HEME FOR ETMATON OF POPULATON MEAN ABTRAT Nada gh Thaku Kalpaa adav fo Mahmacal ccs (M)

More information

Exponentiated Lomax Geometric Distribution: Properties and Applications

Exponentiated Lomax Geometric Distribution: Properties and Applications Expoetated Lomax Geometc Dstbuto: Popetes ad Applcatos Amal Solma Hassa Mathematcal Statstcs Cao Uvesty Isttute of Statstcal Studes ad Reseach Egypt d.amalelmoslamy@gmal.com Mawa Abd-Allah Mathematcal

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

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

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

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 study on Ricci soliton in S -manifolds.

A study on Ricci soliton in S -manifolds. IO Joual of Mathmatc IO-JM -IN: 78-578 p-in: 9-765 olum Iu I Ja - Fb 07 PP - wwwojoualo K dyavath ad Bawad Dpatmt of Mathmatc Kuvmpu vtyhaaahatta - 577 5 hmoa Kaataa Ida Abtact: I th pap w tudy m ymmtc

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

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

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

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t Cla ot fo EE6318/Phy 6383 Spg 001 Th doumt fo tutoal u oly ad may ot b opd o dtbutd outd of EE6318/Phy 6383 tu 7 Dffuo Ou flud quato that w dvlopd bfo a: f ( )+ v v m + v v M m v f P+ q E+ v B 13 1 4 34

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

CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING SCHEME (TNTRDSS) INDEXED THROUGH BASIC QUALITY LEVELS

CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING SCHEME (TNTRDSS) INDEXED THROUGH BASIC QUALITY LEVELS Intnatonal Rsach Jounal of Engnng and Tchnology (IRJET) -ISSN: 2395-0056 Volum: 03 Issu: 02 Fb-2016 www.jt.nt p-issn: 2395-0072 CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING

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

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

φ (x,y,z) in the direction of a is given by

φ (x,y,z) in the direction of a is given by UNIT-II VECTOR CALCULUS Dectoal devatve The devatve o a pot ucto (scala o vecto) a patcula decto s called ts dectoal devatve alo the decto. The dectoal devatve o a scala pot ucto a ve decto s the ate o

More information

Linear Perturbation Bounds of the Continuous-Time LMI-Based H Quadratic Stability Problem for Descriptor Systems

Linear Perturbation Bounds of the Continuous-Time LMI-Based H Quadratic Stability Problem for Descriptor Systems UGRN DE OF ENE ERNE ND NFORON EHNOOGE Volu No 4 ofa a ubao ouds of h ouous- -asd H uadac ably obl fo Dscpo yss dy ochv chcal Uvsy of ofa Faculy of uoacs Dpa of yss ad ool 756 ofa Eal ayochv@u-sofa.bg bsac

More information

School of Aerospace Engineering Origins of Quantum Theory. Measurements of emission of light (EM radiation) from (H) atoms found discrete lines

School of Aerospace Engineering Origins of Quantum Theory. Measurements of emission of light (EM radiation) from (H) atoms found discrete lines Ogs of Quatu Thoy Masuts of sso of lght (EM adato) fo (H) atos foud dsct ls 5 4 Abl to ft to followg ss psso ν R λ c λwavlgth, νfqucy, cspd lght RRydbg Costat (~09,7677.58c - ),,, +, +,..g.,,.6, 0.6, (Lya

More information

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues

Boyce/DiPrima 9 th ed, Ch 7.6: Complex Eigenvalues BocDPm 9 h d Ch 7.6: Compl Egvlus Elm Dffl Equos d Boud Vlu Poblms 9 h do b Wllm E. Boc d Rchd C. DPm 9 b Joh Wl & Sos Ic. W cosd g homogous ssm of fs od l quos wh cos l coffcs d hus h ssm c b w s ' A

More information

Review of Vector Algebra

Review of Vector Algebra apt HPTE EIEW OF ETO LGE vw of cto lgba.. cto.. Dfto of a cto Dfto: vcto s a uatt tat posss bot magtu a cto a obs t paalllogam law of ao. ommutatv: D D Ut vcto:.. Scala Pouct Dot Pouct cos W a t magtu

More information

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring Best Lea Ubased Estmatos of the hee Paamete Gamma Dstbuto usg doubly ype-ii cesog Amal S. Hassa Salwa Abd El-Aty Abstact Recetly ode statstcs ad the momets have assumed cosdeable teest may applcatos volvg

More information

Regional Prosperity and Public Investment Distribution in Greece

Regional Prosperity and Public Investment Distribution in Greece Rgoal Pospty ad Publc Ivstmt Dstbuto Gc Matha Gak Dpatmt of Plag ad Rgoal Dvlopmt Uvsty of Thssaly, Gc magak@uth.g Safm Polyzos Dpatmt of Plag ad Rgoal Dvlopmt Uvsty of Thssaly, Gc spolyzos@uth.g Labos

More information

Estimation of Parameters of the Exponential Geometric Distribution with Presence of Outliers Generated from Uniform Distribution

Estimation of Parameters of the Exponential Geometric Distribution with Presence of Outliers Generated from Uniform Distribution ustala Joual of Basc ad ppled Sceces, 6(: 98-6, ISSN 99-878 Estmato of Paametes of the Epoetal Geometc Dstbuto wth Pesece of Outles Geeated fom Ufom Dstbuto Pavz Nas, l Shadoh ad Hassa Paza Depatmet of

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

Dual adaptive control of mechanical arm

Dual adaptive control of mechanical arm Itatoal Joual of Avac Rsach Comput Egg & chology (IJARCE Volum 6 Issu 9 Sptmb 07 ISSN: 78 33 Dual aaptv cotol of mchacal am Bgtao Lu Jx Pu Jg Lu Abstact Amg at th fctoal foc a th molg o caus by th chag

More information

A new Family of Distributions Using the pdf of the. rth Order Statistic from Independent Non- Identically Distributed Random Variables

A new Family of Distributions Using the pdf of the. rth Order Statistic from Independent Non- Identically Distributed Random Variables Iteratoal Joural of Cotemporary Mathematcal Sceces Vol. 07 o. 8 9-05 HIKARI Ltd www.m-hkar.com https://do.org/0.988/jcms.07.799 A ew Famly of Dstrbutos Usg the pdf of the rth Order Statstc from Idepedet

More information

Convolution of Generated Random Variable from. Exponential Distribution with Stabilizer Constant

Convolution of Generated Random Variable from. Exponential Distribution with Stabilizer Constant Appld Mamacal Scc Vol 9 5 o 9 78-789 HIKARI Ld wwwm-acom p://dxdoog/988/am5559 Covoluo of Gad Radom Vaabl fom Expoal Dbuo w Sablz Coa Dod Dvao Maa Lufaa Oaa ad Maa Aa Dpam of Mamac Facul of Mamac ad Naual

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

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

χ be any function of X and Y then

χ be any function of X and Y then We have show that whe we ae gve Y g(), the [ ] [ g() ] g() f () Y o all g ()() f d fo dscete case Ths ca be eteded to clude fuctos of ay ube of ado vaables. Fo eaple, suppose ad Y ae.v. wth jot desty fucto,

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

and integrated over all, the result is f ( 0) ] //Fourier transform ] //inverse Fourier transform

and integrated over all, the result is f ( 0) ] //Fourier transform ] //inverse Fourier transform NANO 70-Nots Chapt -Diactd bams Dlta uctio W d som mathmatical tools to dvlop a physical thoy o lcto diactio. Idal cystals a iiit this, so th will b som iiitis lii about. Usually, th iiit quatity oly ists

More information

Compact Tripple U-Shaped Slot Loaded Circular Disk Patch Antenna for Bluetooth and WLAN Application

Compact Tripple U-Shaped Slot Loaded Circular Disk Patch Antenna for Bluetooth and WLAN Application 9 VOL.6, NO., MACH Compact ppl U-Shapd Slot Loadd Ccula Dsk Patch Ata fo Blutooth ad WLAN Applcato J. A. Asa, Auag Msha, N. P. Yadav, P. Sgh, B.. Vshvakama Dpatmt of Elctocs & Commucato Uvsty of Allahabad,

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

On Five-Parameter Lomax Distribution: Properties and Applications

On Five-Parameter Lomax Distribution: Properties and Applications O Fve-Paamete Lomax Dstbuto: Popetes ad Applcatos M. E. Mead Depatmet of Statstcs ad Isuace Faculty of Commece, Zagazg Uvesty, Egypt Mead999@gmal.com Abstact A fve-paamete cotuous model, called the beta

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

Robust Regression Analysis for Non-Normal Situations under Symmetric Distributions Arising In Medical Research

Robust Regression Analysis for Non-Normal Situations under Symmetric Distributions Arising In Medical Research Joual of Mode Appled Statstcal Methods Volume 3 Issue Atcle 9 5--04 Robust Regesso Aalyss fo No-Nomal Stuatos ude Symmetc Dstbutos Asg I Medcal Reseach S S. Gaguly Sulta Qaboos Uvesty, Muscat, Oma, gaguly@squ.edu.om

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

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

Record Values from Size-Biased Pareto Distribution and a Characterization

Record Values from Size-Biased Pareto Distribution and a Characterization Iteatoal Joual o Egeeg Reseach ad Geeal Scece Volume, Issue 4, Jue-July, 4 ISSN 9-73 Recod Values om Sze-Based Paeto Dtbuto ad a Chaactezato Shakla Bash, Mu Ahmad Asstat Poesso, Kad College o Wome, Lahoe

More information

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES AYMPTOTIC AD TOLERACE D-MODELLIG I ELATODYAMIC OF CERTAI THI-WALLED TRUCTURE B. MICHALAK Cz. WOŹIAK Dpartmt of tructural Mchacs Lodz Uvrsty of Tchology Al. Poltrchk 6 90-94 Łódź Polad Th objct of aalyss

More information

Elaboration of a MATLB Program to Model Axisymmetric Shells

Elaboration of a MATLB Program to Model Axisymmetric Shells Pocdgs o th Wold Cogss o Egg 0 Vol I WCE 0, July 4-6, 0, odo, U.K. Elaboato o a MAB Poga to Modl Axsytc Shlls AMADI Djaal, ABIOD Bach, ad C. A. D Mllo 3 Abstact h objctv o ths wok s th sttg uc wok o two

More information

multipath channel Li Wei, Youyun Xu, Yueming Cai and Xin Xu

multipath channel Li Wei, Youyun Xu, Yueming Cai and Xin Xu Robust quncy ost stmato o OFDM ov ast vayng multpath channl L W, Youyun Xu, Yumng Ca and Xn Xu Ths pap psnts a obust ca quncy ost(cfo stmaton algothm sutabl o ast vayng multpath channls. Th poposd algothm

More information

GTOC9: Results from the National University of Defense Technology

GTOC9: Results from the National University of Defense Technology GTOC9: Rsults om th Natoal Uvsty o Ds Tchology Yazhog Luo *, Yuh Zhu, Ha Zhu, Zh Yag, Shua Mou, J Zhag, Zhjag Su, ad Ju Lag Collg o Aospac Scc ad Egg, Natoal Uvsty o Ds Tchology, Chagsha 4173, Cha Abstact:

More information

Consistency of the Maximum Likelihood Estimator in Logistic Regression Model: A Different Approach

Consistency of the Maximum Likelihood Estimator in Logistic Regression Model: A Different Approach ISSN 168-8 Joural of Statstcs Volum 16, 9,. 1-11 Cosstcy of th Mamum Lklhood Estmator Logstc Rgrsso Modl: A Dffrt Aroach Abstract Mamuur Rashd 1 ad Nama Shfa hs artcl vstgats th cosstcy of mamum lklhood

More information

Advanced Mechanics of Mechanical Systems

Advanced Mechanics of Mechanical Systems dvacd Mchac of Mchacal Stm Lctu: Pofo k Mkkola, Ph.D., Lappata Uvt of cholog, Flad. ocat Pofo Shaopg Ba, Ph.D., albog Uvt. ocat Pofo Mchal Skpp d, Ph.D., albog Uvt. M. S. d: dvacd Mchac of Mchacal Stm

More information

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1 Scholas Joual of Egeeg ad Techology (SJET) Sch. J. Eg. Tech. 0; (C):669-67 Scholas Academc ad Scetfc Publshe (A Iteatoal Publshe fo Academc ad Scetfc Resouces) www.saspublshe.com ISSN -X (Ole) ISSN 7-9

More information

Bayesian Test for Lifetime Performance Index of Ailamujia Distribution Under Squared Error Loss Function

Bayesian 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 information

A NEW MODIFIED GENERALIZED ODD LOG-LOGISTIC DISTRIBUTION WITH THREE PARAMETERS

A NEW MODIFIED GENERALIZED ODD LOG-LOGISTIC DISTRIBUTION WITH THREE PARAMETERS A NEW MODIFIED GENERALIZED ODD LOG-LOGISTIC DISTRIBUTION WITH THREE PARAMETERS Arbër Qoshja 1 & Markela Muça 1. Departmet of Appled Mathematcs, Faculty of Natural Scece, Traa, Albaa. Departmet of Appled

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

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor Cotol Syt ctu 8 Root ocu Clacal Cotol Pof. Eugo Schut hgh Uvty Root ocu Cotoll Plat R E C U Y - H C D So Y C C R C H Wtg th loo ga a w a ttd tackg th clod-loo ol a ga va Clacal Cotol Pof. Eugo Schut hgh

More information

Math Tricks. Basic Probability. x k. (Combination - number of ways to group r of n objects, order not important) (a is constant, 0 < r < 1)

Math Tricks. Basic Probability. x k. (Combination - number of ways to group r of n objects, order not important) (a is constant, 0 < r < 1) Math Trcks r! Combato - umbr o was to group r o objcts, ordr ot mportat r! r! ar 0 a r a s costat, 0 < r < k k! k 0 EX E[XX-] + EX Basc Probablt 0 or d Pr[X > ] - Pr[X ] Pr[ X ] Pr[X ] - Pr[X ] Proprts

More information

Optimal Progressive Group-Censoring Plans for. Weibull Distribution in Presence. of Cost Constraint

Optimal Progressive Group-Censoring Plans for. Weibull Distribution in Presence. of Cost Constraint It J Cotmp Mat Sccs Vol 7 0 o 7 337-349 Optmal Progrssv Group-Csorg Plas for Wbull Dstrbuto Prsc of Cost Costrat A F Atta Dpartmt of Matmatcal Statstcs Isttut of Statstcal Stus & Rsarc Caro Uvrsty Egypt

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

In the name of Allah Proton Electromagnetic Form Factors

In the name of Allah Proton Electromagnetic Form Factors I th a of Allah Poto Elctoagtc o actos By : Maj Hazav Pof A.A.Rajab Shahoo Uvsty of Tchology Atoc o acto: W cos th tactos of lcto bas wth atos assu to b th gou stats. Th ct lcto ay gt scatt lastcally wth

More information

( V ) 0 in the above equation, but retained to keep the complete vector identity for V in equation.

( V ) 0 in the above equation, but retained to keep the complete vector identity for V in equation. Cuvlna Coodnats Outln:. Otogonal cuvlna coodnat systms. Dffntal opatos n otogonal cuvlna coodnat systms. Dvatvs of t unt vctos n otogonal cuvlna coodnat systms 4. Incompssbl N-S quatons n otogonal cuvlna

More information

Instrumentation for Characterization of Nanomaterials (v11) 11. Crystal Potential

Instrumentation for Characterization of Nanomaterials (v11) 11. Crystal Potential Istumtatio o Chaactizatio o Naomatials (v). Cystal Pottial Dlta uctio W d som mathmatical tools to dvlop a physical thoy o lcto diactio om cystal. Idal cystals a iiit this, so th will b som iiitis lii

More information

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19)

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19) TOTAL INTRNAL RFLTION Kmacs pops Sc h vcos a coplaa, l s cosd h cd pla cocds wh h X pla; hc 0. y y y osd h cas whch h lgh s cd fom h mdum of hgh dx of faco >. Fo cd agls ga ha h ccal agl s 1 ( /, h hooal

More information

A comparative study between ridit and modified ridit analysis

A comparative study between ridit and modified ridit analysis Ameca Joual o Theoetcal ad Appled Statstcs 3; (6): 48-54 Publshed ole Decembe, 3 (http://www.scecepublshggoup.com/j/ajtas) do:.648/j.ajtas.36.3 A compaatve stud betwee dt ad moded dt aalss Ebuh Godda Uwawuoe,

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

Chapter 6. pn-junction diode: I-V characteristics

Chapter 6. pn-junction diode: I-V characteristics Chatr 6. -jucto dod: -V charactrstcs Tocs: stady stat rsos of th jucto dod udr ald d.c. voltag. ucto udr bas qualtatv dscusso dal dod quato Dvatos from th dal dod Charg-cotrol aroach Prof. Yo-S M Elctroc

More information

THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS

THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS RELIK ; Paha 5. a 6.. THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS Daa Bílová Abstact Commo statstcal methodology fo descpto of the statstcal samples

More information

A Random Graph Model for Power Law Graphs

A Random Graph Model for Power Law Graphs A Random Gaph Modl fo Pow Law Gaphs Wllam Allo, Fan Chung, and Lnyuan Lu CONTNTS. Intoducton. A Random Gaph Modl 3. Th Connctd Componnts 4. Th Szs of Connctd Componnts n Ctan Rangs fo 5. On th Sz of th

More information

On Jackson's Theorem

On Jackson's Theorem It. J. Cotm. Math. Scics, Vol. 7, 0, o. 4, 49 54 O Jackso's Thom Ema Sami Bhaya Datmt o Mathmatics, Collg o Educatio Babylo Uivsity, Babil, Iaq mabhaya@yahoo.com Abstact W ov that o a uctio W [, ], 0

More information

A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES

A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES Mathematcal ad Computatoal Applcatos, Vol. 3, No., pp. 9-36 008. Assocato fo Scetfc Reseach A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES Ahmed M.

More information

A Stochastic Approximation Iterative Least Squares Estimation Procedure

A Stochastic Approximation Iterative Least Squares Estimation Procedure Joural of Al Azhar Uvrst-Gaza Natural Sccs, 00, : 35-54 A Stochastc Appromato Itratv Last Squars Estmato Procdur Shahaz Ezald Abu- Qamar Dpartmt of Appld Statstcs Facult of Ecoomcs ad Admstrato Sccs Al-Azhar

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 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 information

Chapter 7 Varying Probability Sampling

Chapter 7 Varying Probability Sampling Chapte 7 Vayg Pobablty Samplg The smple adom samplg scheme povdes a adom sample whee evey ut the populato has equal pobablty of selecto. Ude ceta ccumstaces, moe effcet estmatos ae obtaed by assgg uequal

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

Note on the Computation of Sample Size for Ratio Sampling

Note on the Computation of Sample Size for Ratio Sampling Not o th Computato of Sampl Sz for ato Samplg alr LMa, Ph.D., PF Forst sourcs Maagmt Uvrst of B.C. acouvr, BC, CANADA Sptmbr, 999 Backgroud ato samplg s commol usd to rduc cofdc trvals for a varabl of

More information

L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES

L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Sees A, OF THE ROMANIAN ACADEMY Volume 8, Numbe 3/27,. - L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES

More information

Digital Image Processing

Digital Image Processing Impa Cog odo Dpatmt of Ectca ad Ectoc Egg Dgta Imag Pocssg PART IMAGE ENHANCEMENT Acadmc sposb D. Taa STATHAKI Room 8 Et. 469 Ema: t.statha@mpa.ac.u http://www.commsp..c.ac.u/~taa/ . Pmas. Spata doma mthods

More information

FUZZY MULTINOMIAL CONTROL CHART WITH VARIABLE SAMPLE SIZE

FUZZY MULTINOMIAL CONTROL CHART WITH VARIABLE SAMPLE SIZE A. Paduaga et al. / Iteatoal Joual of Egeeg Scece ad Techology (IJEST) FUZZY MUTINOMIA CONTRO CHART WITH VARIABE SAMPE SIZE A. PANDURANGAN Pofesso ad Head Depatmet of Compute Applcatos Vallamma Egeeg College,

More information

Almost all Cayley Graphs Are Hamiltonian

Almost all Cayley Graphs Are Hamiltonian Acta Mathmatca Sca, Nw Srs 199, Vol1, No, pp 151 155 Almost all Cayly Graphs Ar Hamltoa Mg Jxag & Huag Qogxag Abstract It has b cocturd that thr s a hamltoa cycl vry ft coctd Cayly graph I spt of th dffculty

More information

Recent Advances in Computers, Communications, Applied Social Science and Mathematics

Recent Advances in Computers, Communications, Applied Social Science and Mathematics Recet Advaces Computes, Commucatos, Appled ocal cece ad athematcs Coutg Roots of Radom Polyomal Equatos mall Itevals EFRAI HERIG epatmet of Compute cece ad athematcs Ael Uvesty Cete of amaa cece Pa,Ael,4487

More information