• Title/Summary/Keyword: null hypothesis

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On Testing Monotonicity of Mean Residual Life from Randomly Censored Data

  • Lim, Jae-Hak;Koh, Jai-Sang
    • ETRI Journal
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    • v.18 no.3
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    • pp.207-213
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    • 1996
  • This paper proposes a new nonparametric test for testing the null hypothesis that the MRL is constant against the alternative hypothesis that the MRL is decreasing (increasing) for ramdomly censored data. The proposed test statistic is a L-statistic, and we use L-statistic theory to establish its asymptotic normality of the test statistic. We discuss the efficiency loss due to censoring and also calculate the asymptotic relative efficiencies of our test statistic with respect to the Chen, Hollander and Langberg's test for several alternatives.

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Robust Unit Root Tests with an Innovation Variance Break

  • Oh, Yu-Jin
    • Communications for Statistical Applications and Methods
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    • v.19 no.1
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    • pp.177-182
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    • 2012
  • A structural break in the level as well as in the innovation variance has often been exhibited in economic time series. In this paper we propose robust unit root tests based on a sign-type test statistic when a time series has a shift in its level and the corresponding volatility. The proposed tests are robust to a wide class of partially stationary processes with heavy-tailed errors, and have an exact binomial null distribution. Our tests are not affected by the size or location of the break. We set the structural break under the null and the alternative hypotheses to relieve a possible vagueness in interpreting test results in empirical work. The null hypothesis implies a unit root process with level shifts and the alternative connotes a stationary process with level shifts. The Monte Carlo simulation shows that our tests have stable size than the OLSE based tests.

Test procedures for the mean and variance simultaneously under normality

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.23 no.6
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    • pp.563-574
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    • 2016
  • In this study, we propose several simultaneous tests to detect the difference between means and variances for the two-sample problem when the underlying distribution is normal. For this, we apply the likelihood ratio principle and propose a likelihood ratio test. We then consider a union-intersection test after identifying the likelihood statistic, a product of two individual likelihood statistics, to test the individual sub-null hypotheses. By noting that the union-intersection test can be considered a simultaneous test with combination function, also we propose simultaneous tests with combination functions to combine individual tests for each sub-null hypothesis. We apply the permutation principle to obtain the null distributions. We then provide an example to illustrate our proposed procedure and compare the efficiency among the proposed tests through a simulation study. We discuss some interesting features related to the simultaneous test as concluding remarks. Finally we show the expression of the likelihood ratio statistic with a product of two individual likelihood ratio statistics.

Testing Homogeneity for Random Effects in Linear Mixed Model

  • Ahn, Chul H.
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.403-414
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    • 2000
  • A diagnostic tool for testing homogeneity for random effects is proposed in unbalanced linear mixed model based on score statistic. The finite sample behavior of the test statistic is examined using Monte Carlo experiments examine the chi-square approximation of the test statistic under the null hypothesis.

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Some Nonparametric Tests for Change-points with Epidemic Alternatives

  • Kim, Kyung-Moo
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.427-434
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    • 1997
  • The purpose of this paper is to discuss distribution-free tests of hypothesis that the random samples are identically distributed against the epidemic alternative. But most tests that have been considered are depended only on specific null distribution. Two nonparametric tests are considered and compared with a likelihood ratio test by the empirical powers.

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Testing Homogeneity of Errors in Unbalanced Random Effects Linear Model

  • Ahn, Chul H.
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.603-613
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    • 2001
  • A test based on score statistic is derived for detecting homoscedasticity of errors in unbalanced random effects linear model. A small simulation study is performed 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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A Bivariate Two Sample Rank Test for Mixture Distributions

  • Songyong Sim;Seungmin Lee
    • Communications for Statistical Applications and Methods
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    • v.3 no.2
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    • pp.197-204
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    • 1996
  • We consider a two sample rank test for a bivariate mixture distribution based on Johnson's quantile score. The test statistic is simple to calculate and the exact distribution under the null hypothesis is obtained. A numerical example is given.

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Performance Comparison of Out-Of-Vocabulary Word Rejection Algorithms in Variable Vocabulary Word Recognition (가변어휘 단어 인식에서의 미등록어 거절 알고리즘 성능 비교)

  • 김기태;문광식;김회린;이영직;정재호
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.2
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    • pp.27-34
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    • 2001
  • Utterance verification is used in variable vocabulary word recognition to reject the word that does not belong to in-vocabulary word or does not belong to correctly recognized word. Utterance verification is an important technology to design a user-friendly speech recognition system. We propose a new utterance verification algorithm for no-training utterance verification system based on the minimum verification error. First, using PBW (Phonetically Balanced Words) DB (445 words), we create no-training anti-phoneme models which include many PLUs(Phoneme Like Units), so anti-phoneme models have the minimum verification error. Then, for OOV (Out-Of-Vocabulary) rejection, the phoneme-based confidence measure which uses the likelihood between phoneme model (null hypothesis) and anti-phoneme model (alternative hypothesis) is normalized by null hypothesis, so the phoneme-based confidence measure tends to be more robust to OOV rejection. And, the word-based confidence measure which uses the phoneme-based confidence measure has been shown to provide improved detection of near-misses in speech recognition as well as better discrimination between in-vocabularys and OOVs. Using our proposed anti-model and confidence measure, we achieve significant performance improvement; CA (Correctly Accept for In-Vocabulary) is about 89%, and CR (Correctly Reject for OOV) is about 90%, improving about 15-21% in ERR (Error Reduction Rate).

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The Convergence of Poverty Rates among States across the U.S.

  • Kim, Yung-Keun
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.3
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    • pp.131-142
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    • 2018
  • Since income growth rate and poverty level are related, there is a possibility that the poverty rate may converge in the long run steady state as well. If the poverty rate converges, then for this study the state that begins with the high poverty rate would have a higher poverty reduction rate. To examine the convergence of poverty rate among the US states, this study uses two times series methodologies. First, in order to prevent the power loss from ignoring the structural break when testing for a unit root in a single time series, this study employs the newly developed panel LM unit root tests with level and trend shifts. The results of unit root tests of the log of poverty rate without allowing for structural breaks show that twenty six states reject the null hypothesis of unit root test for the ADF test, twenty five states for the LM test, and thirty five states for the RALS-LM test. The result of unit root tests that allow one structural break shows that the null hypothesis of a unit root test is rejected for twenty two states with the LM test, and thirty three states with the RALS-LM test. This supports poverty rates are converging among US states.

The Impact of Implementation of ISO9000: 2000 on Technology Improvement: A Case study

  • Shahalizadeh, Mohammad;Mostabseri, Mohammad
    • Industrial Engineering and Management Systems
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    • v.7 no.3
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    • pp.228-244
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    • 2008
  • ISO9000 set of standards has been widely applied in Iranian Automotive manufacturing industry. Regarding the effects of TQM and ISO9000 set of standards various studies have been conducted and different quantitative conclusions have been made. Due to lack of quantitative information, in many of the cases, using qualitative information becomes the best option. The qualitative nature of data in such cases, requires qualitative analysis methods that might lead to some challenging computational issues. This paper examines the impact of ISO9000: 2000 certification and its perceived benefits for an automotive manufacturing company. Using an empirical approach, the paper seeks to ascertain if certification has indeed improved the performance of the company. Our null hypothesis rotates around the effect of ISO9000: 2000 on the 4W's of an enterprise. To carry out the research, first we developed a couple of questionnaires including all criteria of ISO9000 and 4W's. Second, the questionnaires were discussed with two researchers knowledgeable in the field, and then submitted to the quality practitioners and executives of Iran Khodro Enterprise-a leading company in Iranian automotive manufacturing industry. Finally the null hypothesis was tested and the technology improvement dimensions were ranked through nonparametric tests. The results illustrated a reasonable cause and effect relationship, suggesting that ISO9000: 2000 has positive effect on the 4W's of company result. In this work we investigate the effect as technology improvement viz., the improvement of techno-ware, human-ware, info-ware, and organ-ware.