• Title/Summary/Keyword: record value statistics

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A Bayesian Approach for Record Value Statistics Model Using Nonhomogeneous Poisson Process

  • Kiheon Choi;Hee chual Kim
    • Communications for Statistical Applications and Methods
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    • v.4 no.1
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    • pp.259-269
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    • 1997
  • Bayesian inference for a record value statistics(RVS) model of nonhomogeneous Poisson process is considered. We seal with Bayesian inference for double exponential, Gamma, Rayleigh, Gumble RVS models using Gibbs sampling and Metropolis algorithm and also explore Bayesian computation and model selection.

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ON RELATIONS FOR QUOTIENT MOMENTS OF THE GENERALIZED PARETO DISTRIBUTION BASED ON RECORD VALUES AND A CHARACTERIZATION

  • Kumar, Devendra
    • Journal of applied mathematics & informatics
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    • v.31 no.3_4
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    • pp.327-336
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    • 2013
  • Generalized Pareto distributions play an important role in re-liability, extreme value theory, and other branches of applied probability and statistics. This family of distribution includes exponential distribution, Pareto distribution, and Power distribution. In this paper we establish some recurrences relations satisfied by the quotient moments of the upper record values from the generalized Pareto distribution. Further a char-acterization of this distribution based on recurrence relations of quotient moments of record values is presented.

Bayesian Approach for Software Reliability Models (소프트웨어 신뢰모형에 대한 베이지안 접근)

  • Choi, Ki-Heon
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.119-133
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    • 1999
  • A Markov Chain Monte Carlo method is developed to compute the software reliability model. We consider computation problem for determining of posterior distibution in Bayseian inference. Metropolis algorithms along with Gibbs sampling are proposed to preform the Bayesian inference of the Mixed model with record value statistics. For model determiniation, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions. A numerical example with simulated data set is given.

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RECURRENCE RELATIONS FOR QUOTIENT MOMENTS OF GENERALIZED PARETO DISTRIBUTION BASED ON GENERALIZED ORDER STATISTICS AND CHARACTERIZATION

  • Kumar, Devendra
    • Journal of the Chungcheong Mathematical Society
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    • v.27 no.3
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    • pp.347-361
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    • 2014
  • Generalized Pareto distribution play an important role in reliability, extreme value theory, and other branches of applied probability and statistics. This family of distribution includes exponential distribution, Pareto or Lomax distribution. In this paper, we established exact expressions and recurrence relations satised by the quotient moments of generalized order statistics for a generalized Pareto distribution. Further the results for quotient moments of order statistics and records are deduced from the relations obtained and a theorem for characterizing this distribution is presented.

ON CHARACTERIZATIONS OF CONTINUOUS DISTRIBUTIONS BY CONDITIONAL EXPECTATIONS OF UPPER RECORD VALUES

  • Jin, Hyun-Woo;Lee, Min-Young
    • Journal of the Chungcheong Mathematical Society
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    • v.25 no.3
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    • pp.501-505
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    • 2012
  • In this paper, general classes of continuous distributions are characterized by considering the conditional expectations of functions of upper record statistics. The specific distribution considered as a particular case of the general class of distribution are Exponential, Exponential Power(EP), Inverse Weibull, Beta Gumbel, Modified Weibull(MW), Weibull, Pareto, Power, Singh-Maddala, Gumbel, Rayleigh, Gompertz, Extream value 1, Beta of the first kind, Beta of the second kind and Lomax.

A BAYESIAN APPROACH FOR A DECOMPOSITION MODEL OF SOFTWARE RELIABILITY GROWTH USING A RECORD VALUE STATISTICS

  • Choi, Ki-Heon;Kim, Hee-Cheul
    • Journal of applied mathematics & informatics
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    • v.8 no.1
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    • pp.243-252
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    • 2001
  • The points of failure of a decomposition process are defined to be the union of the points of failure from two component point processes for software reliability systems. Because sampling from the likelihood function of the decomposition model is difficulty, Gibbs Sampler can be applied in a straightforward manner. A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For model determination, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. A numerical example with a simulated data set is given.

Predicting depth value of the future depth-based multivariate record

  • Samaneh Tata;Mohammad Reza Faridrohani
    • Communications for Statistical Applications and Methods
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    • v.30 no.5
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    • pp.453-465
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    • 2023
  • The prediction problem of univariate records, though not addressed in multivariate records, has been discussed by many authors based on records values. There are various definitions for multivariate records among which depth-based records have been selected for the aim of this paper. In this paper, by means of the maximum likelihood and conditional median methods, point and interval predictions of depth values which are related to the future depth-based multivariate records are considered on the basis of the observed ones. The observations derived from some elements of the elliptical distributions are the main reason of studying this problem. Finally, the satisfactory performance of the prediction methods is illustrated via some simulation studies and a real dataset about Kermanshah city drought.

An Adaptive Failure Rate Change-Point Model for Software Reliability

  • Jeong, Kwang-Mo
    • International Journal of Reliability and Applications
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    • v.2 no.3
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    • pp.199-207
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    • 2001
  • The failure rate functions between successive failures are of concatenated form. We allow the parameters of failure rate function change after a certain failure and its fixing. We confine out attention to a model wherein the interfailure times are described by its failure rate function. We suggest an adaptive failure rate function with a change-point under the assumption that interfailure times are record value statistics from a Weibull distribution. The proposed model will be applied through a practical example of software failure data.

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Suggestion of batter ability index in Korea baseball - focusing on the sabermetrics statistics WAR (한국프로야구에서 타자능력지수 제안 - 대체선수대비승수(WAR)을 중심으로)

  • Lee, Jea-Young;Kim, Hyeon-Gyu
    • The Korean Journal of Applied Statistics
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    • v.29 no.7
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    • pp.1271-1281
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    • 2016
  • Wins above replacement (WAR) is one of the most widely used statistic among sabermatrics statistics that measure the ability of a batter in baseball. WAR has a great advantage that is to represent the attack power of the player and the base running ability, defensive ability as a single value. In this study, we proposed a hitter ability index using the sabermetrics statistics that can replace WAR based on Korea Baseball Record Data of the last three years (2013-2015). First, we calculated Batter ability index through the arithmetic mean method, the weighted average method, principal component regression and selected the method that had high correlation with WAR.

A Study of Infinite Failure NHPP Software Reliability Growth Model base on Record Value Statistics with Gamma Family of Lifetime Distribution (수명분포가 감마족인 기록값 통계량에 기초한 무한고장 NHPP 소프트웨어 신뢰성장 모형에 관한 비교 연구)

  • Kim, Hee-Cheul;Sin, Hyun-Cheul
    • Convergence Security Journal
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    • v.6 no.3
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    • pp.145-153
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    • 2006
  • Infinite failure NHPP models for a record value satisfies mode proposed in the literature exhibit either monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, propose comparative study of software reliability model using Erlang distribution, Rayleigh and Gumbel distribution. Equations to estimate the parameters using maximum likelihood estimation of infinite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing distribution, we used to the special pattern. Analysis of failure data set using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

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