• Title/Summary/Keyword: Asymptotic test

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On Estimating of Kullback-Leibler Information Function using Three Step Stress Accelerated Life Test

  • Park, Byung-Gu;Yoon, Sang-Chul;Cho, Ji-Young
    • International Journal of Reliability and Applications
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    • v.1 no.2
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    • pp.155-165
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    • 2000
  • In this paper, we propose some estimators of Kullback- Leibler Information functions using the data from three step stress accelerated life tests. This acceleration model is assumed to be a tampered random variable model. Some asymptotic properties of proposed estimators are proved. Simulations are performed for comparing the small sample properties of the proposed estimators under use condition of accelerated life test.

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Optimum Design of Accelerated Degradation Tests for Lognormal Distribution

  • Lee, Nak-Young
    • Journal of Korean Society for Quality Management
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    • v.23 no.1
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    • pp.29-40
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    • 1995
  • This paper considers the problem of optimally designing accelerated degradation tests in which the performance value of a specimen is measured only at one of three test conditions for a given exposure time. For the product having lognormally distributed performance, the optimum plan-low stress level and sample proportion allocated to each test condition - is obtained, which minimize the asymptotic variance of maximum likelihood estimator of a stated quantile at design stress. An illustrative example for the optimum plan is given.

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Large Sample Test for Independence in the Bivariate Pareto Model with Censored Data

  • Cho, Jang-Sik;Lee, Jea-Man;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.2
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    • pp.377-383
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    • 2003
  • In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

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GOODNESS OF FIT TESTS BASED ON DIVERGENCE MEASURES

  • Pasha, Eynollah;Kokabi, Mohsen;Mohtashami, Gholam Reza
    • Journal of applied mathematics & informatics
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    • v.26 no.1_2
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    • pp.177-189
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    • 2008
  • In this paper, we have considered an investigation on goodness of fit tests based on divergence measures. In the case of categorical data, under certain regularity conditions, we obtained asymptotic distribution of these tests. Also, we have proposed a modified test that improves the rate of convergence. In continuous case, we used our modified entropy estimator [10], for Kullback-Leibler information estimation. A comparative study based on simulation results is discussed also.

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On Effect of Nonnormality on Size of Test for Dimensionality in Discriminant Analysis

  • Changha Hwang
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.25-30
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    • 1996
  • In discriminant analysis the procedures commonly used to estimate the dimensionality involve testing a sequence of dimensionality hypotheses. There is a problem with the size of the test since dimensionality hypotheses are tested sequentially and thus they are actually conditional tests. The focus of this paper is to investigate in asymptotic sense what happens to the sequential testing procedure if the assumption of normality does not hold.

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A Test Procedure for Change in Level Occurring at Unknown Points

  • Lee, Jae-Chang;Song, Il-Seong
    • Journal of the Korean Statistical Society
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    • v.18 no.1
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    • pp.38-45
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    • 1989
  • A procedure is considered to the problem of testing whether there exist changes in location at possibly two points in a sequence of independent random variables which are successively drawn from normal population. A test statistics based on modified likelihood ratio is proposed and its asymptotic null distribution is derived through the stochastic process representation. A small sample power comparison is made by Monte Carlo method.

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A Heuristic Approach for Approximating the ARL of the CUSUM Chart

  • Kim, Byung-Chun;Park, Chang-Soon;Park, Young-Hee;Lee, Jae-Heon
    • Journal of the Korean Statistical Society
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    • v.23 no.1
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    • pp.89-102
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    • 1994
  • A new method for approximating the average run length (ARL) of cumulative sum (CUSUM) chart is proposed. This method uses the conditional expectation for the test statistic before the stopping time and its asymptotic conditional density function. The values obtained by this method are compared with some other methods in normal and exponential case.

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Heteroscedasticity of Random Effects in Crossover Design

  • Ahn, Chul-H.
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.79-83
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    • 2002
  • A phase III clinical trial of a new drug for neutropenia induced by chemotherapy is presented and consider adding random effects in crossover design which was used in the clinical study. The diagnostics for its heteroscedasticity based on score statistic is derived for detecting homoscedasticity of errors in crossover design. A small simulation study is peformed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

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Test for Independence in Bivariate Weibull Model under Bivariate Random Censorship

  • Cho, Jang-Sik;Cho, Kil-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.789-797
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    • 2003
  • In this paper, we consider two components system which have bivariate weibull model with bivariate random censored data. We proposed large sample test for independence based on maximum likelihood estimator and relative frequency estimator, respectively. Also we derive asymptotic properties for the large sample tests and present a numerical study.

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Weighted Least Absolute Error Estimation of Regression Parameters

  • Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • v.8 no.1
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    • pp.23-36
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    • 1979
  • In the multiple linear regression model a class of weighted least absolute error estimaters, which minimize the sum of weighted absolute residuals, is proposed. It is shown that the weighted least absolute error estimators with Wilcoxon scores are equivalent to the Koul's Wilcoxon type estimator. Therefore, the asymptotic efficiency of the proposed estimator with Wilcoxon scores relative to the least squares estimator is the same as the Pitman efficiency of the Wilcoxon test relative to the Student's t-test. To find the estimates the iterative weighted least squares method suggested by Schlossmacher is applicable.

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