• Title/Summary/Keyword: Statistical testing

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Test for Independence in Bivariate Pareto Model with Bivariate Random Censored Data

  • Cho, Jang-Sik;Kwon, Yong-Man;Choi, Seung-Bae
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.1
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    • pp.31-39
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    • 2004
  • In this paper, we consider two components system which the lifetimes follow bivariate pareto model with bivariate random censored data. We assume that the censoring times are independent of the lifetimes of the two components. We develop large sample test for testing independence between two components. Also we present a simulation study which is the test based on asymptotic normal distribution in testing independence.

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A NEW UDB-MRL TEST FOR WITH UNKNOWN

  • Na, Myung-Hwan
    • Journal of Korean Society for Quality Management
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    • v.30 no.4
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    • pp.78-85
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    • 2002
  • The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, a new test statistic for testing whether or not the mean residual life changes its trend is developed. It is assumed that neither the change point nor the proportion at which the trend change occurs is known. The asymptotic null distribution of test statistic is established and asymptotic critical values of the asymptotic null distribution is obtained. Monte Carlo simulation is used to compare the proposed test with previously known tests.

Analysis on Reports of Statistical Testing for Mean Differences in Articles in the Korean Journal of Women Health Nursing (여성건강간호학회지에 게재된 차이검정을 이용한 논문의 통계활용 분석)

  • Jun, Eun-Mi;Lee, Eun-Hee;Kim, Jeung-Im;Kang, Hee-Sun;Oh, Hyun-Ei;Lee, Eun-Joo;Cheon, Suk-Hee
    • Women's Health Nursing
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    • v.17 no.4
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    • pp.388-394
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    • 2011
  • Purpose: This study was done to evaluate the accuracy and adequacy of research studies reporting statistical testing for mean differences in studies of the Korean Journal of Women Health. Methods: Among articles published in the journal from 2007 to 2009, 75 studies using t-test, $x^2$-test, and ANOVA were identified. The studies were evaluated using structured analysis format for adequacy of research title, accuracy of statistical methods and presentation styles, and errors in reported statistical outcomes. Results: In this study, the research titles generally reflected the purpose of research and study designs. Thus the research titles were quite comprehensive. Also, there was compatibility between the research purpose and research design. Most important though, many errors were identified in the tables of results of the statistical analysis in articles published from 2004 to 2006. Conclusion: Over six years, 2004 to 2009, accuracy and adequacy of research studies has improved in many aspects. In order to enhance the completeness of the published papers and to be an internationally recognized nursing journal, close attention of the researchers, reviewers and editors is necessary to avoid errors and present adequate and accurate research.

The Significance Test on the AHP-based Alternative Evaluation: An Application of Non-Parametric Statistical Method (AHP를 이용한 대안 평가의 유의성 분석: 비모수적 통계 검정 적용)

  • Park, Joonsoo;Kim, Sung-Chul
    • The Journal of Society for e-Business Studies
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    • v.22 no.1
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    • pp.15-35
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    • 2017
  • The method of weighted sum of evaluation using AHP is widely used in feasibility analysis and alternative selection. Final scores are given in forms of weighted sums and the alternative with largest score is selected. With two alternatives, as in feasibility analysis, the final score greater than 0.5 gives the selection but there remains a question that how large is large enough. KDI suggested a concept of 'grey area' where scores are between 0.45 and 0.55 in which decisions are to be made with caution, but it lacks theoretical background. Statistical testing was introduced to answer the question in some studies. It was assumed some kinds of probability distribution, but did not give the validity on them. We examine the various cases of weighted sum of evaluation score and show why the statistical testing has to be introduced. We suggest a non-parametric testing procedure which does not assume a specific distribution. A case study is conducted to analyze the validity of our suggested testing procedure. We conclude our study with remarks on the implication of analysis and the future way of research development.

On Testing Fisher's Linear Discriminant Function When Covariance Matrices Are Unequal

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.325-337
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    • 1993
  • This paper propose two test statistics which enable us to proceed the variable selection in Fisher's linear discriminant function for the case of heterogeneous discrimination with equal training sample size. Simultaneous confidence intervals associated with the test are also given. These are exact and approximate results. The latter is based upon an approximation of a linear sum of Wishart distributions with unequal scale matrices. Using simulated sampling experiments, powers of the two tests have been tabulated, and power comparisons have been made between them.

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Distribution-Free k-Sample Tests for Ordered Alternatives of Scale Parameters

  • Jeong, Kwang-Mo;Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • v.17 no.2
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    • pp.61-80
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    • 1988
  • For testing homogeneity of scale parameters aginst ordered alternatives, some nonparametric test statistics based on pairwise ranking method are proposed. The proposed tests are distribution-free. The asymptotic distributions of the proposed statistcs are also investigated. It is shown that the Pitman efficiencies of the proposed rank tests are the same as those of the corresponding two-sample rank tests in the scale problem. A small-sample Monte Carlo study is also performed. The results show that the proposed tests are robust and efficient.

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Empirical Bayes Test for the Exponential Parameter with Censored Data

  • Wang, Lichun
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.213-228
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    • 2008
  • Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.

Tests for Normal Mean Change with the Mean Difference

  • Kim, Jaehee;Yun, Pilkyoung
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.353-359
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    • 2003
  • This paper deals with the problem of testing mean change with one change-point with the normal random variables. We propose a test with the mean difference for change in a location parameter. A power comparison study of various change-point test statistics is performed via Monte Carlo simulation with S-plus software.

TESTING FOR SMOOTH TRANSITION NONLINEARITY IN PARTIALLY NONSTATIONARY VECTOR AUTOREGRESSIONS

  • Seo, Byeong-Seon
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.257-274
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    • 2007
  • This paper considers the tests for the presence of smooth transition non-linearity in the partially nonstationary vector autoregressive model. The transition parameters cannot be identified under the null hypothesis of linearity, and therefore this paper develops the tests for smooth transition nonlinearity, the associated asymptotic theory and the bootstrap inference. The Monte Carlo simulation evidence shows that the bootstrap inference generates moderate size and power performances.

A Study on Bayesian p-values

  • Hwnag, Hyungtae;Oh, Heejung
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.725-732
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    • 2002
  • P-values are often perceived as measurements of degree of compatibility between the current data and the hypothesized model. In this paper, a new concept of Bayesian p-values is proposed and studied under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical p-values in the sense of using the concept of significance level. The performances of the proposed Bayesian p-values are compared with those of the classical p-values through several examples.