Analysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed
|
|
- John Bond
- 5 years ago
- Views:
Transcription
1 Amerca Joural of Mathematcs ad Statstcs. ; (: -8 DOI:.593/j.ajms.. Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted M. Gherda, M. Boushaba, Departmet of Mathematcs, Faculty of sceces, Uversty of Jjel, Algera Laboratory of mathematcal modelg ad smulato, Uversty of Costate Route daï-el-bey Costate, Algera Abstract A (--out-of-: G system s a system that cossts of compoets ad works f ad oly f (- compoets amog the work smultaeously. The system ad each of ts compoets ca oly oe of two states: workg or faled. Whe a compoet fals t s put uder repar ad the other compoets stay the "workg" state wth adjusted rates of falure. After repar, a compoet works as ew ad ts actual lfetme s the same as tally. If the faled compoet s repared before aother compoet fals, the (- compoets recover ther tal lfetme. The lfetme ad tme of repar are depedet. I ths paper, we propose a techque to calculate the mea tme of repar, the probablty of varous states of our system ad ts avalablty by usg the theory of dstrbuto. Keywords G System, System Avalablty, Reparable System, Falure Rates, Dstrbuto Theory. Itroducto The k-out-of- system structure s a very popular type of redudat fault-tolerat systems. It fds wde applcatos both dustral ad mltary systems. These systems clude the multdsplay system cockpts, the multege system a arplae, ad the multpurpose system a hydrau-lc cotrol system. I a commucatos system wth three trasmtters, the average message load may be such that at least two trasmtters must be operatoal at all tmes or crtcal messages may be lost. The trasmsso subsystem fuctos as a -out-of-3: G system. Systems wth spares may also be represeted by the k-out-of- system model. I the case of a automoble wth four tres, for example, usually oe addtoal spare tre s carred o the vehcle. Thus, the vehcle ca be drve as log as at least 4-out-of-5 tres are good codto. I ths paper, we cosder the reparable case where k-,.e. a reparable (--out-of-: G system whch works f ad oly f at least (- compoets amog the work smultaeously. Few papers aalyze ths kd of systems, Gaver[] ad Jack[] cosder a -ut parallel system, Gherda & Boushaba[3] aalyze a -out-of-3 system whe the dstrbutos of the tme of falure ad the tme of repar are geeral. I ths work, we geeralze the result of Gherda & Boushaba[3]: We suppose that all compoets ad the system have ether oe of two states: a "workg" state or a "faled" state. whe Correspodg author: mboushabafr@yahoo.fr (M. Boushaba ublshed ole at Copyrght Scetfc & Academc ublshg. All Rghts Reserved a compoet fals t s put uder repar ad the other compoets stay the "workg" state wth adjusted rates of falure. After repar, the compoet works as ew ad ts actual lfetme s the same as tally. If the faled compoet s repared before aother compoet fals, the (- compoets recover ther tal lfetme. The lfetme ad tme of repar are depedet. I ths paper, we propose a techque to calculate the mea tme of falure, the probablty of varous states of our system ad ts avalablty by usg the theory of dstrbuto. Fally, we gve some umercal examples.. Notato C : compoet of the system,,,..., E s : the state of system, s,,. We say that the system s the state E s at tme t f there are exactly s faled compoets at tme t. : rate of falure of compoet C whe all compoets j, ( j are workg. : rate of falure of compoet C whe compoet j,( j s "faled". X : tme of repar of compoet C. ; ( t;x : the desty of the probablty of evet: " oly the compoet C s fals at tme t ad t s uder repar sce a tme x" ; ( t;x : the desty of probablty of evet : "Two
2 M. Gherda et al.: Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted compoets C j ad C k are "faled" ad compoets C are the "workg" state at tme t sce tme x; {,...,}/{j; k}. ( t : robablty of the evet: "No compoet s "faled" at tme t" ϕ ( s : The Laplace trasform of the dstrbuto of T A: The avalablty of the system G : the dstrbuto fucto of u : hazard rate fucto x X ad G G u( y dy u( y dy dg G e ad e u. lm t x lm t,x,, t,. t x lm t,x, t, G, G : the Laplace trasform of ( f : the verse Laplace trasform of f : Covoluto product 3. Model x G ad G Let N (t ad X (t be two stochastc process wth cotuous tme such that N (t s. If the system s the state E s ad X (t x f the compoet whch faled at tme t s uder repar sce date x: Cosder the evet N (t + dt ; t ca be obtaed ( + dfferet ways: - At tme t, N (t ad durg the terval of tme [t; t + dt] there are o falures, the probablty of ths evet s t dt Or at tme t, N (t ad durg the terval of tme [t; t + dt]; the faled compoet C s repared, the probablty of ths evet s t dt t,x u x + dt;,,...,., The the probablty of ths evet s ( t + dt r ( N ( t + dt ( t dt+ j t j dt dt, ( t, x u j j whe dt we obta t d ( t +, u dt ( Cosder the evet N (t + dt ; t ca be obtaed dfferet ways : - N (t + dt ad X (t + dt x + dt: f N (t, X (t x ad the repar of the faled compoet s ot fshed at tme t + dt: the probablty of ths evet oted by t + dt, x + dt s gve by:, t + dt,x + dt,, ( t, x j + u dt+ ( dt f t > x j j otherwse whe dt we obta: θ( t x, + θ( t x, t x ( j + u θ( t x, j j where θ s the dcator fucto. - Or N (t + dt ad X (t + dt dt: f N (t ad a falure occurs durg the terval of tme [t; t + dt]: Ths case s gve by the tal codtos:, ( t, ad (. Our system ca be represeted by the fgure. Fgure
3 Amerca Joural of Mathematcs ad Statstcs. ; (: Calculato of the State robabltes of a System 4.. Calculato of ( t ad, ( t,x Let ( s ad, ( t ad, fucto ( t x s,x be the Laplace trasform of t,x respectvely. Because the dcator θ s a regular dstrbuto, we ca use the dervato of ( the sese of dstrbuto: θ( t x, + θ( t x, t x j + u θ( t x, j j By takg the Laplace trasform of the two members of ths last equalty we obta s,x, x (3 ( s exp s + j x exp u ( y dy j j Now, takg the Laplace trasform of the two members of the equalty (:, ( s,x ( s exp s + j x G (4 j j we ote that, ( s,x ( s G s+ j x+ j j by applyg a proposto [4] page 5 to, ( s,x, whch verfes ths majorato, we obta d θ ( t x, f dt ( s,x where f s the verse trasform of ( s,x, We ote that s the Laplace trasform of the s covoluto product. By usg (4:, s, ( s,x sx exp x j G x s e j s j s exp x j G ( t δ ( t x t j j where δ s the Drac fucto. The verse Laplace trasform of, s,x s gve by: d exp x j G ( t δ ( t x t dt j j exp x j G ( t (5 j j Now, we obta: ( t ( t + ( t G j t j j By takg the Laplace trasform of the two members of ths equalty we obta: ( s s+ G j j j by usg the verse Laplace trasformed, we obta: ( t exp G j t j j ad ( t exp x j G f t x, > j j otherwse lm t ad Wth codtos t x lm t,x t, t t,
4 4 M. Gherda et al.: Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted 4.. Calculato of ( x, The evet N(t + dt ca be obtaed two ways:. N(t, X(x+dt dt; X(t ad durg the terval of tme [t; t + dt], oe compoet amog the workg compoets fals ad the repar of the faled compoet s ot fshed. Ths evet has the probablty:,, j dt u dt+ ( dt j j, j dt f x < t j j otherwse. Or N(t, X(x + dt dt, ad ay repar are fshed ad o falure occurs durg the terval of tme [t; t + dt] :Ths evet has the probablty:, + j dt f x < t j j otherwse So, t + dt,x +, u j dt+ j j, + u j dt f x < t j j whe dt we obta:, t,x, t,x + t x u, u, f x < t j j Otherwse, by usg the Laplace trasform ad the tal codto (t; t, we obta: s + u, ( s,x +, ( s,x x, ( s,x j j j Oe soluto of ths equato s gve by:, ( s,x exp ( α k + j, ( s,x exp ( α j j where α s a prmtve of [ s u ] (6 + ad k a costat. Now by usg the covoluto product, the soluto of (6 s gve by, ( s,x exp ( sx exp u. j ( s j j K + exp s + j j j xg exp ( sx exp ( u fally, we obta :
5 Amerca Joural of Mathematcs ad Statstcs. ; (: -8 5 δ s,x K t x exp u x +, ( s δ ( t x exp u j j j exp j x j j by usg the verse Laplace trasform ad the tal codto (t; t (K, we obta, xe x G ( x G j j j exp t GI j j j ad t,x t,x,, exp t G j j j G j j j G j j j 5. Characterstcs of the System 5.. Mea Tme of Falure LetΦ be the Laplace trasform of, ( t,x : Φ ( s, ( s,x Φ ( s exp x j G j j s+ G j j j exp x j G j j s+ G j j j ( G j j j j Fally j j Φ E T s+ G j j j ( G j j j j j j G j j j 5.. Avalablty of the System Let A(t, x the avalablty of the system. The ( t A(t, x +, + exp j G exp G j t j j j j
6 6 M. Gherda et al.: Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted 5.3. Case of No Idetcal Compoets I the stablty case, we obta the followg equatos for the system: u ( x, j d, j + u ( x, j j d, + u ( x, j, ( x j j Ths system becomes: + G (,, j j j j,, j j j exp x G x G x exp x,, j j j by usg ths hypothess: ( u x,, j j j (codtos at the lmts, we obta +, +, j Gj j j j j j ad +,j + j So,j + j exp x j G j j,j + G exp x j j j E( X,j I we ca wrte the soluto the followg form:, +, + - G j j j j j j -, E( X j fally, we derve:, B C + D Where Gj ke X j k j j k B G j j k k j k C Gj Gj k k j j k ad D ( j G j( + j k 4 j j j j 5.4. Case of N Idetcal Compoets I the stablty case ( t, we obta the followg equatos for the system: u ( x ( x
7 Amerca Joural of Mathematcs ad Statstcs. ; (: -8 7 d ( + u ( x d + u ( x ( by usg the tal codtos ad codtos at the lmts : ( ad ( + u x, we obta + ( -G (( + + By the same argumet as the o detcal case, we derve - G (( G (( E( X - - G ( G ( + [ -6] Remark : whe 3, we obta the result gve page [3] 6. Numercal Examples Cosder the case where ad the stablty case ( t. Whe the compoets are o detcal, the equatos of the system are: ( + u, ( x, 3 + u, x,, exp 3 x G x,, G x exp 3 x ( ( By combg these equatos, we obta: + x u x, 3, 3, A + where ( ( 3 ( + G ( ( G ( G G 3 G 3- G 3- ( + G ( ( G ( ( ( E( X ( G G G G G 3- I the detcal case, we have ( G G ( + E( X G ( G ( + E( X G ( + G ( A. G ( + E( X I the followg, we wll gve some umercal examples whe we cosder the cases: -X s costat, X E(X, G ( -exp (- -X follows the expoetal law G + - X follows the law 6 We ote m G + 6 f.375 ad.75, the values of E(X for dfferet values of m ad dfferet laws of X are gve Tables ad, respectvely: Table. The values of E(X for dfferet values of m ad dfferet laws of X.(.375 X Γ ( / 6 m Xct X exp Table. The values of E(X for dfferet values of m ad dfferet laws of X.(.75 X Γ ( / 6 m Xct X exp The values of the probablty states ad the avalablty, for varous laws of X, are gve the Tables 3, 4 ad 5.
8 8 M. Gherda et al.: Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted Table 3. m The values of probablty y states ad avalablty for X costat Table 4. The values of probablty y states ad avalablty for X exp ( m Coclusos The work preseted here s a study of a (--out-of-: G reparable system whose compoets are depedet ad ot detcal. The durato of compoet falure ad that of the repars are radom varables followg expoetal laws ad arbtrary laws respectvely. The ovelty ths cotrbuto s the use of the followg, very realstc hypothess: whe a compoet fals, the falure rates of all other compoets chage; aturally, whe that compoet s repared, these same compoets recover ther tal falure rates. To the authors kowledge, prevous works dd ot tackle ths case from the same agle as ths study. The authors beleve that dfferetato of dstrbutos s the techque best suted for the calculato of the avalablty ad of the other characterstcs of ths kd of systems. Addtoally, the choce of the techque to use s beleved to be judcous ad has ever bee used before ths kd of stuatos. More geerally, the case k-out-of- systems remas a ope problem that deserves more explorato. A A Table 5. The values of probablty y states ad avalablty for X Γ 6 m ACKNOWLEDGEMENTS The authors are grateful for rofessor Fabrzo Rugger from IMATI (Italy for the valuable suggestos ad commets whch have cosderably mproved the presetato of the paper. We ackowledge, wth thaks, the costructve commets made by the referees whch helped to ehace the qualty of ths paper. REFERENCES [] D.. Gaver, Tme to falure of paralled systems wth repar, IEEE trasacto o relablty, vol R-, 96 [] N. Jack, Aalyss of a reparable -ut parallel redudat system wth repar, IEEE trasacto o relablty, vol R-35, 986 [3] M. Gherda ad M. Boushaba, Aalyss of a reparable -out-of-3 system wth falure ad repas tmes arbtrarly dstrbuted, proccedg of 3th ISSAT teratoal coferece, Seattle, Washgto, USA, august -4 7, eds: T. Nakagara, H. ham ad S. Yamada, pp 96- [4] L. Shwartz, Méthodes mathématques pour les sceces physques, 966, eds Herma ars [5] K. N. Fracs Leug, Y. L. Zhag, K. K. La, Aalyss for a two-dssmlar-compoet cold stadby reparable system wth repar prorty, Relablty Egeerg ad system safety, vol. 96 ssue, November, pp [6] Y. L. Zhag, G. J. Wag, A geometrc process repar model for a reparable cold stadby system wth prorty use ad repar, Relablty Egeerg ad system safety, vol. 94 ssue, No-vember 9, pp A
Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions
Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur
More informationLecture 2 - What are component and system reliability and how it can be improved?
Lecture 2 - What are compoet ad system relablty ad how t ca be mproved? Relablty s a measure of the qualty of the product over the log ru. The cocept of relablty s a exteded tme perod over whch the expected
More informationFunctions of Random Variables
Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,
More informationBayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information
Malaysa Joural of Mathematcal Sceces (): 97- (9) Bayes Estmator for Expoetal Dstrbuto wth Exteso of Jeffery Pror Iformato Hadeel Salm Al-Kutub ad Noor Akma Ibrahm Isttute for Mathematcal Research, Uverst
More informationComparing 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 informationChapter 14 Logistic Regression Models
Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as
More informationMultivariate Transformation of Variables and Maximum Likelihood Estimation
Marquette Uversty Multvarate Trasformato of Varables ad Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Assocate Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 03 by Marquette Uversty
More informationSimulation Output Analysis
Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5
More informationSpecial Instructions / Useful Data
JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth
More informationLINEAR REGRESSION ANALYSIS
LINEAR REGRESSION ANALYSIS MODULE V Lecture - Correctg Model Iadequaces Through Trasformato ad Weghtg Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur Aalytcal methods for
More informationAnalysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems
Char for Network Archtectures ad Servces Prof. Carle Departmet of Computer Scece U Müche Aalyss of System Performace IN2072 Chapter 5 Aalyss of No Markov Systems Dr. Alexader Kle Prof. Dr.-Ig. Georg Carle
More informationA New Family of Transformations for Lifetime Data
Proceedgs of the World Cogress o Egeerg 4 Vol I, WCE 4, July - 4, 4, Lodo, U.K. A New Famly of Trasformatos for Lfetme Data Lakhaa Watthaacheewakul Abstract A famly of trasformatos s the oe of several
More informationComparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates
Joural of Moder Appled Statstcal Methods Volume Issue Artcle 8 --03 Comparso of Parameters of Logormal Dstrbuto Based O the Classcal ad Posteror Estmates Raja Sulta Uversty of Kashmr, Sragar, Ida, hamzasulta8@yahoo.com
More informationDynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load
Dyamc Aalyss of Axally Beam o Vsco - Elastc Foudato wth Elastc Supports uder Movg oad Saeed Mohammadzadeh, Seyed Al Mosayeb * Abstract: For dyamc aalyses of ralway track structures, the algorthm of soluto
More informationAnalysis of Variance with Weibull Data
Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad
More informationSolving Constrained Flow-Shop Scheduling. Problems with Three Machines
It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632
More informationUNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS
UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted
More informationVOL. 3, NO. 11, November 2013 ISSN ARPN Journal of Science and Technology All rights reserved.
VOL., NO., November 0 ISSN 5-77 ARPN Joural of Scece ad Techology 0-0. All rghts reserved. http://www.ejouralofscece.org Usg Square-Root Iverted Gamma Dstrbuto as Pror to Draw Iferece o the Raylegh Dstrbuto
More informationUnimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods
Malaysa Umodalty Joural Tests of Mathematcal for Global Optmzato Sceces (): of 05 Sgle - 5 Varable (007) Fuctos Usg Statstcal Methods Umodalty Tests for Global Optmzato of Sgle Varable Fuctos Usg Statstcal
More informationCHAPTER VI Statistical Analysis of Experimental Data
Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca
More informationAnalysis of Lagrange Interpolation Formula
P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal
More informationANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK
Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION
More informationComplete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables
Joural of Sceces, Islamc Republc of Ira 8(4): -6 (007) Uversty of Tehra, ISSN 06-04 http://sceces.ut.ac.r Complete Covergece ad Some Maxmal Iequaltes for Weghted Sums of Radom Varables M. Am,,* H.R. Nl
More informationArithmetic Mean and Geometric Mean
Acta Mathematca Ntresa Vol, No, p 43 48 ISSN 453-6083 Arthmetc Mea ad Geometrc Mea Mare Varga a * Peter Mchalča b a Departmet of Mathematcs, Faculty of Natural Sceces, Costate the Phlosopher Uversty Ntra,
More informationBAYESIAN ESTIMATOR OF A CHANGE POINT IN THE HAZARD FUNCTION
Mathematcal ad Computatoal Applcatos, Vol. 7, No., pp. 29-38, 202 BAYESIAN ESTIMATOR OF A CHANGE POINT IN THE HAZARD FUNCTION Durdu Karasoy Departmet of Statstcs, Hacettepe Uversty, 06800 Beytepe, Akara,
More informationEstimation of the Loss and Risk Functions of Parameter of Maxwell Distribution
Scece Joural of Appled Mathematcs ad Statstcs 06; 4(4): 9- http://www.scecepublshggroup.com/j/sjams do: 0.648/j.sjams.060404. ISSN: 76-949 (Prt); ISSN: 76-95 (Ole) Estmato of the Loss ad Rsk Fuctos of
More informationApplied Mathematics and Materials
Appled Mathematcs ad Materals O a Two-No-Idetcal Stadby Reparable System wth Imperfect Repar MOHAMMED A. HAJEEH, ABDUL-WAHAB ALOTHMAN 2 Techo-Ecoomcs Dvso Kuwat Isttute for Scetfc Research P.O. Box 24885;
More informationUNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS
UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:
More information{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:
Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed
More informationAnalyzing Fuzzy System Reliability Using Vague Set Theory
Iteratoal Joural of Appled Scece ad Egeerg 2003., : 82-88 Aalyzg Fuzzy System Relablty sg Vague Set Theory Shy-Mg Che Departmet of Computer Scece ad Iformato Egeerg, Natoal Tawa versty of Scece ad Techology,
More informationIJOART. Copyright 2014 SciResPub.
Iteratoal Joural of Advacemets Research & Techology, Volume 3, Issue 10, October -014 58 Usg webull dstrbuto the forecastg by applyg o real data of the umber of traffc accdets sulama durg the perod (010-013)
More informationLecture 02: Bounding tail distributions of a random variable
CSCI-B609: A Theorst s Toolkt, Fall 206 Aug 25 Lecture 02: Boudg tal dstrbutos of a radom varable Lecturer: Yua Zhou Scrbe: Yua Xe & Yua Zhou Let us cosder the ubased co flps aga. I.e. let the outcome
More informationDiscrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b
CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package
More informationChapter 5 Properties of a Random Sample
Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample
More informationNon-uniform Turán-type problems
Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at
More informationA Remark on the Uniform Convergence of Some Sequences of Functions
Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut
More informationA New Method for Decision Making Based on Soft Matrix Theory
Joural of Scetfc esearch & eports 3(5): 0-7, 04; rtcle o. JS.04.5.00 SCIENCEDOMIN teratoal www.scecedoma.org New Method for Decso Mag Based o Soft Matrx Theory Zhmg Zhag * College of Mathematcs ad Computer
More informationMaximum Likelihood Estimation
Marquette Uverst Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Coprght 08 b Marquette Uverst Maxmum Lkelhood Estmato We have bee sag that ~
More informationA NEW LOG-NORMAL DISTRIBUTION
Joural of Statstcs: Advaces Theory ad Applcatos Volume 6, Number, 06, Pages 93-04 Avalable at http://scetfcadvaces.co. DOI: http://dx.do.org/0.864/jsata_700705 A NEW LOG-NORMAL DISTRIBUTION Departmet of
More informationIterated Logarithm Laws on GLM Randomly Censored with Random Regressors and Incomplete Information #
Appled Mathematcs 363-368 do:.436/am..343 ublshed Ole March (http://www.scr.org/joural/am) Iterated Logarthm Laws o GLM Radomly Cored wth Radom Regrsors ad Icomplete Iformato # Abstract Qag Zhu Zhhog ao
More informationChapter 3 Sampling For Proportions and Percentages
Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys
More informationSummary of the lecture in Biostatistics
Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the
More informationInternational Journal of Mathematical Archive-5(8), 2014, Available online through ISSN
Iteratoal Joural of Mathematcal Archve-5(8) 204 25-29 Avalable ole through www.jma.fo ISSN 2229 5046 COMMON FIXED POINT OF GENERALIZED CONTRACTION MAPPING IN FUZZY METRIC SPACES Hamd Mottagh Golsha* ad
More information5 Short Proofs of Simplified Stirling s Approximation
5 Short Proofs of Smplfed Strlg s Approxmato Ofr Gorodetsky, drtymaths.wordpress.com Jue, 20 0 Itroducto Strlg s approxmato s the followg (somewhat surprsg) approxmato of the factoral,, usg elemetary fuctos:
More informationEVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM
EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM Jose Javer Garca Moreta Ph. D research studet at the UPV/EHU (Uversty of Basque coutry) Departmet of Theoretcal
More informationf f... f 1 n n (ii) Median : It is the value of the middle-most observation(s).
CHAPTER STATISTICS Pots to Remember :. Facts or fgures, collected wth a defte pupose, are called Data.. Statstcs s the area of study dealg wth the collecto, presetato, aalyss ad terpretato of data.. The
More informationOptimal Strategy Analysis of an N-policy M/E k /1 Queueing System with Server Breakdowns and Multiple Vacations
Iteratoal Joural of Scetfc ad Research ublcatos, Volume 3, Issue, ovember 3 ISS 5-353 Optmal Strategy Aalyss of a -polcy M/E / Queueg System wth Server Breadows ad Multple Vacatos.Jayachtra*, Dr.A.James
More informationProbabilistic Meanings of Numerical Characteristics for Single Birth Processes
A^VÇÚO 32 ò 5 Ï 206 c 0 Chese Joural of Appled Probablty ad Statstcs Oct 206 Vol 32 No 5 pp 452-462 do: 03969/jss00-426820605002 Probablstc Meags of Numercal Characterstcs for Sgle Brth Processes LIAO
More informationCubic 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 informationDerivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations
Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat
More informationbest estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best
Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg
More informationModified Moment Estimation for a Two Parameter Gamma Distribution
IOSR Joural of athematcs (IOSR-J) e-issn: 78-578, p-issn: 39-765X. Volume 0, Issue 6 Ver. V (Nov - Dec. 04), PP 4-50 www.osrjourals.org odfed omet Estmato for a Two Parameter Gamma Dstrbuto Emly rm, Abel
More informationSome Notes on the Probability Space of Statistical Surveys
Metodološk zvezk, Vol. 7, No., 200, 7-2 ome Notes o the Probablty pace of tatstcal urveys George Petrakos Abstract Ths paper troduces a formal presetato of samplg process usg prcples ad cocepts from Probablty
More informationAvailability Equivalence Factors of a General Repairable Parallel-Series System
ppled Mathematcs 04 5 73-73 Publshed Ole Jue 04 cres. http://www.scrp.org/joural/am http://dx.do.org/0.436/am.04.564 valablty Equvalece Factors of a Geeral Reparable Parallel-eres ystem bdelfattah Mustafa
More informationGenerating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function
7659, Eglad, UK Joural of Iformato ad Computg Scece Vol. 2, No. 3, 2007, pp. 9-96 Geeratg Multvarate Noormal Dstrbuto Radom Numbers Based o Copula Fucto Xaopg Hu +, Jam He ad Hogsheg Ly School of Ecoomcs
More informationLecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model
Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The
More informationLecture 07: Poles and Zeros
Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto
More informationResearch Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings
Hdaw Publshg Corporato Iteratoal Joural of Mathematcs ad Mathematcal Sceces Volume 009, Artcle ID 391839, 9 pages do:10.1155/009/391839 Research Artcle A New Iteratve Method for Commo Fxed Pots of a Fte
More informationEconometric Methods. Review of Estimation
Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators
More information1 Solution to Problem 6.40
1 Soluto to Problem 6.40 (a We wll wrte T τ (X 1,...,X where the X s are..d. wth PDF f(x µ, σ 1 ( x µ σ g, σ where the locato parameter µ s ay real umber ad the scale parameter σ s > 0. Lettg Z X µ σ we
More informationClass 13,14 June 17, 19, 2015
Class 3,4 Jue 7, 9, 05 Pla for Class3,4:. Samplg dstrbuto of sample mea. The Cetral Lmt Theorem (CLT). Cofdece terval for ukow mea.. Samplg Dstrbuto for Sample mea. Methods used are based o CLT ( Cetral
More informationApplication of Generating Functions to the Theory of Success Runs
Aled Mathematcal Sceces, Vol. 10, 2016, o. 50, 2491-2495 HIKARI Ltd, www.m-hkar.com htt://dx.do.org/10.12988/ams.2016.66197 Alcato of Geeratg Fuctos to the Theory of Success Rus B.M. Bekker, O.A. Ivaov
More informationRandom Variate Generation ENM 307 SIMULATION. Anadolu Üniversitesi, Endüstri Mühendisliği Bölümü. Yrd. Doç. Dr. Gürkan ÖZTÜRK.
adom Varate Geerato ENM 307 SIMULATION Aadolu Üverstes, Edüstr Mühedslğ Bölümü Yrd. Doç. Dr. Gürka ÖZTÜK 0 adom Varate Geerato adom varate geerato s about procedures for samplg from a varety of wdely-used
More information9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d
9 U-STATISTICS Suppose,,..., are P P..d. wth CDF F. Our goal s to estmate the expectato t (P)=Eh(,,..., m ). Note that ths expectato requres more tha oe cotrast to E, E, or Eh( ). Oe example s E or P((,
More informationA New Measure of Probabilistic Entropy. and its Properties
Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com
More informationMEASURES OF DISPERSION
MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda
More informationRandom Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois
Radom Varables ECE 313 Probablty wth Egeerg Alcatos Lecture 8 Professor Rav K. Iyer Uversty of Illos Iyer - Lecture 8 ECE 313 Fall 013 Today s Tocs Revew o Radom Varables Cumulatve Dstrbuto Fucto (CDF
More informationBounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy
Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled
More information( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model
Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch
More informationTHE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA
THE ROYAL STATISTICAL SOCIETY 3 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA PAPER I STATISTICAL THEORY & METHODS The Socety provdes these solutos to assst caddates preparg for the examatos future years ad
More informationNumerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract
Numercal Smulatos of the Complex Moded Korteweg-de Vres Equato Thab R. Taha Computer Scece Departmet The Uversty of Georga Athes, GA 002 USA Tel 0-542-2911 e-mal thab@cs.uga.edu Abstract I ths paper mplemetatos
More informationResearch Article Some Strong Limit Theorems for Weighted Product Sums of ρ-mixing Sequences of Random Variables
Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 2009, Artcle ID 174768, 10 pages do:10.1155/2009/174768 Research Artcle Some Strog Lmt Theorems for Weghted Product Sums of ρ-mxg Sequeces
More informationA 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 informationOn generalized fuzzy mean code word lengths. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India
merca Joural of ppled Mathematcs 04; (4): 7-34 Publshed ole ugust 30, 04 (http://www.scecepublshggroup.com//aam) do: 0.648/.aam.04004.3 ISSN: 330-0043 (Prt); ISSN: 330-006X (Ole) O geeralzed fuzzy mea
More informationConfidence Intervals for Double Exponential Distribution: A Simulation Approach
World Academy of Scece, Egeerg ad Techology Iteratoal Joural of Physcal ad Mathematcal Sceces Vol:6, No:, 0 Cofdece Itervals for Double Expoetal Dstrbuto: A Smulato Approach M. Alrasheed * Iteratoal Scece
More informationDependence In Network Reliability
Depedece I Network Relablty Nozer D. Sgpurwalla George Washgto Uversty Washgto, DC, U.S.A. ozer@reasearch.crc.gwu.edu Abstract It s farly easy to calculate the relablty of a etwork wth depedet odes va
More informationReal Time Study of a Identical Repairable Elements with Constant Failure and Repair Rates
Proceedgs of the Iteratoal MultCoferece of Egeers ad Computer Scetsts 009 Vol II IMECS 009, March 8-0, 009, Hog Kog Real Tme Study of a out of System: Idetcal Reparable Elemets wth Costat Falure ad Repar
More informationLecture 9: Tolerant Testing
Lecture 9: Tolerat Testg Dael Kae Scrbe: Sakeerth Rao Aprl 4, 07 Abstract I ths lecture we prove a quas lear lower boud o the umber of samples eeded to do tolerat testg for L dstace. Tolerat Testg We have
More informationA tighter lower bound on the circuit size of the hardest Boolean functions
Electroc Colloquum o Computatoal Complexty, Report No. 86 2011) A tghter lower boud o the crcut sze of the hardest Boolea fuctos Masak Yamamoto Abstract I [IPL2005], Fradse ad Mlterse mproved bouds o the
More informationBootstrap Method for Testing of Equality of Several Coefficients of Variation
Cloud Publcatos Iteratoal Joural of Advaced Mathematcs ad Statstcs Volume, pp. -6, Artcle ID Sc- Research Artcle Ope Access Bootstrap Method for Testg of Equalty of Several Coeffcets of Varato Dr. Navee
More informationMYUNG HWAN NA, MOON JU KIM, LIN MA
BAYESIAN APPROACH TO MEAN TIME BETWEEN FAILURE USING THE MODULATED POWER LAW PROCESS MYUNG HWAN NA, MOON JU KIM, LIN MA Abstract. The Reewal process ad the No-homogeeous Posso process (NHPP) process are
More informationOrdinary Least Squares Regression. Simple Regression. Algebra and Assumptions.
Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos
More informationThe Generalized Inverted Generalized Exponential Distribution with an Application to a Censored Data
J. Stat. Appl. Pro. 4, No. 2, 223-230 2015 223 Joural of Statstcs Applcatos & Probablty A Iteratoal Joural http://dx.do.org/10.12785/jsap/040204 The Geeralzed Iverted Geeralzed Expoetal Dstrbuto wth a
More informationIS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model
IS 79/89: Comutatoal Methods IS Research Smle Marova Queueg Model Nrmalya Roy Deartmet of Iformato Systems Uversty of Marylad Baltmore Couty www.umbc.edu Queueg Theory Software QtsPlus software The software
More informationCOMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL
Sebasta Starz COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL Abstract The am of the work s to preset a method of rakg a fte set of dscrete radom varables. The proposed method s based o two approaches:
More informationA 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 informationResearch Article A New Derivation and Recursive Algorithm Based on Wronskian Matrix for Vandermonde Inverse Matrix
Mathematcal Problems Egeerg Volume 05 Artcle ID 94757 7 pages http://ddoorg/055/05/94757 Research Artcle A New Dervato ad Recursve Algorthm Based o Wroska Matr for Vadermode Iverse Matr Qu Zhou Xja Zhag
More informationOn Fuzzy Arithmetic, Possibility Theory and Theory of Evidence
O Fuzzy rthmetc, Possblty Theory ad Theory of Evdece suco P. Cucala, Jose Vllar Isttute of Research Techology Uversdad Potfca Comllas C/ Sata Cruz de Marceado 6 8 Madrd. Spa bstract Ths paper explores
More informationThe number of observed cases The number of parameters. ith case of the dichotomous dependent variable. the ith case of the jth parameter
LOGISTIC REGRESSION Notato Model Logstc regresso regresses a dchotomous depedet varable o a set of depedet varables. Several methods are mplemeted for selectg the depedet varables. The followg otato s
More informationBayesian Inferences for Two Parameter Weibull Distribution Kipkoech W. Cheruiyot 1, Abel Ouko 2, Emily Kirimi 3
IOSR Joural of Mathematcs IOSR-JM e-issn: 78-578, p-issn: 9-765X. Volume, Issue Ver. II Ja - Feb. 05, PP 4- www.osrjourals.org Bayesa Ifereces for Two Parameter Webull Dstrbuto Kpkoech W. Cheruyot, Abel
More informationTHE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION
Joural of Scece ad Arts Year 12, No. 3(2), pp. 297-32, 212 ORIGINAL AER THE ROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION DOREL MIHET 1, CLAUDIA ZAHARIA 1 Mauscrpt receved: 3.6.212; Accepted
More informationReliability evaluation of distribution network based on improved non. sequential Monte Carlo method
3rd Iteratoal Coferece o Mecatrocs, Robotcs ad Automato (ICMRA 205) Relablty evaluato of dstrbuto etwork based o mproved o sequetal Mote Carlo metod Je Zu, a, Cao L, b, Aog Tag, c Scool of Automato, Wua
More informationBERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler
Mathematcal ad Computatoal Applcatos, Vol. 8, No. 3, pp. 293-300, 203 BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS Aysegul Ayuz Dascoglu ad Nese Isler Departmet of Mathematcs,
More informationLecture 3 Probability review (cont d)
STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto
More informationStudy of Correlation using Bayes Approach under bivariate Distributions
Iteratoal Joural of Scece Egeerg ad Techolog Research IJSETR Volume Issue Februar 4 Stud of Correlato usg Baes Approach uder bvarate Dstrbutos N.S.Padharkar* ad. M.N.Deshpade** *Govt.Vdarbha Isttute of
More informationBayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study
IJIEST Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 5, July 04. Bayes Iterval Estmato for bomal proporto ad dfferece of two bomal proportos wth Smulato Study Masoud Gaj, Solmaz hlmad
More informationarxiv:math/ v1 [math.gm] 8 Dec 2005
arxv:math/05272v [math.gm] 8 Dec 2005 A GENERALIZATION OF AN INEQUALITY FROM IMO 2005 NIKOLAI NIKOLOV The preset paper was spred by the thrd problem from the IMO 2005. A specal award was gve to Yure Boreko
More information22 Nonparametric Methods.
22 oparametrc Methods. I parametrc models oe assumes apror that the dstrbutos have a specfc form wth oe or more ukow parameters ad oe tres to fd the best or atleast reasoably effcet procedures that aswer
More informationX ε ) = 0, or equivalently, lim
Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece
More informationCHAPTER 3 POSTERIOR DISTRIBUTIONS
CHAPTER 3 POSTERIOR DISTRIBUTIONS If scece caot measure the degree of probablt volved, so much the worse for scece. The practcal ma wll stck to hs apprecatve methods utl t does, or wll accept the results
More information