• Title/Summary/Keyword: Kolmogorov Distance

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A Recursive Partitioning Rule for Binary Decision Trees

  • Kim, Sang-Guin
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.471-478
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    • 2003
  • In this paper, we reconsider the Kolmogorov-Smirnoff distance as a split criterion for binary decision trees and suggest an algorithm to obtain the Kolmogorov-Smirnoff distance more efficiently when the input variable have more than three categories. The Kolmogorov-Smirnoff distance is shown to have the property of exclusive preference. Empirical results, comparing the Kolmogorov-Smirnoff distance to the Gini index, show that the Kolmogorov-Smirnoff distance grows more accurate trees in terms of misclassification rate.

KOLMOGOROV DISTANCE FOR MULTIVARIATE NORMAL APPROXIMATION

  • Kim, Yoon Tae;Park, Hyun Suk
    • Korean Journal of Mathematics
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    • v.23 no.1
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    • pp.1-10
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    • 2015
  • This paper concerns the rate of convergence in the multidimensional normal approximation of functional of Gaussian fields. The aim of the present work is to derive explicit upper bounds of the Kolmogorov distance for the rate of convergence instead of Wasserstein distance studied by Nourdin et al. [Ann. Inst. H. Poincar$\acute{e}$(B) Probab.Statist. 46(1) (2010) 45-98].

Two model comparisons of software reliability analysis for Burr type XII distribution

  • An, Jeong-Hyang
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.815-823
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    • 2012
  • In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

Closeness of Lindley distribution to Weibull and gamma distributions

  • Raqab, Mohammad Z.;Al-Jarallah, Reem A.;Al-Mutairi, Dhaifallah K.
    • Communications for Statistical Applications and Methods
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    • v.24 no.2
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    • pp.129-142
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    • 2017
  • In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

The Study for NHPP Software Reliability Model based on Chi-Square Distribution (카이제곱 NHPP에 의한 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.1 s.39
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    • pp.45-53
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    • 2006
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

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ON THE EXISTENCE OF A UNIQUE INVARIANT PROBABILITY FOR A CLASS OF MARKOV PROCESSES

  • Lee, Oesook
    • Bulletin of the Korean Mathematical Society
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    • v.30 no.1
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    • pp.91-97
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    • 1993
  • In this article, we consider the case that S is a topologically complete subspace of $R^{k}$ , and that .GAMMA. is a set of monotone functions on S into S. It is obtained the sugficient condition for the existence of a unique invariant probability to which $P^{(n}$/(x,dy) converges exponentially fast in a metric stronger than the Kolmogorov's distance. This extends the earlier results of Bhattacharya and Lee (1988) who considered the case .GAMMA. a set of nondecreasing functions.tions.

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The study for NHPP Software Reliability Model based on Kappa(2) distribution (Kappa(2) NHPP에 의한 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.689-696
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    • 2005
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

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The Study for ENHPP Software Reliability Growth Model based on Burr Coverage Function (Burr 커버리지 함수에 기초한 ENHPP소프트웨어 신뢰성장모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.4
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    • pp.33-42
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    • 2007
  • Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. From the analysis of mission time, the result of this comparative study shows the excellent performance of Burr coverage model rather than exponential coverage and S-shaped model using NTDS data. This analysis of failure data compared with the Kappa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

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The Study for NHPP Software Reliability Growth Model based on Exponentiated Exponential Distribution (지수화 지수 분포에 의존한 NHPP 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.9-18
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    • 2006
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

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The Study for ENHPP Software Reliability Growth Model Based on Kappa(2) Coverage Function (Kappa(2) 커버리지 함수를 이용한 ENHPP 소프트웨어 신뢰성장모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.12
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    • pp.2311-2318
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    • 2007
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.