• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.355-376
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• 2006

To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.95-103
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• 1998

Azzalini and Bowman proposed the pseudo-likelihood ratio test for checking the linear relationship using kernel regression estimator when the error of the regression model follows the normal distribution. We modify their method with the bootstrap technique to construct a new test, and examine the power of our test through simulation. Our method can be applied to the case where the distribution of the error is not normal.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.235-240
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• 2000

In this paper a test of fit for exponentiality and we propose the estimator of Kullback-Leibler Information functions using the data from accelerated life tests. This acceleration model is assumed to be a tampered random variable model. The procedure is applicable when the exponential parameter based on the data from accelerated life tests is or is not specified under null hypothesis. Using Simulations, the power of the proposed test based on use condition of accelerated life test under alternatives is compared with that of other standard tests in the small sample.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.169-178
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• 1994

Nonparametric tests for comparing two treatments when data are subject to unequal patterns of censorship are discussed. Best precedence test proposed by Slud can be viewed as a nice alternative test comparing with weighted log-rank tests, not to mention the advantage of short experimental period. This research revises some missing parts of Slud's test and examines the asymptotic power of it under the nonproportional hazard alternatives through the simulation. The simulation studies show best precedence test has reasonable power in the sense of robustness under nonproportional hazard alternatives and could be recommended at such situation.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.229-240
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• 2002

Whether to use linear or quadratic model in the analysis of regression data is one of the important problems in classical regression model and measurement error model (MEM). In MEM, four goodness of fit test statistics are available In solving that problem. Two are from the derivation of estimators of quadratic MEM, and one is from that of the general $k^{th}$-order polynomial MEM. The fourth one is derived as a variation of goodness of fit test statistic used in linear MEM. The purpose of this paper is to find the most powerful test statistic among them through the small-scale simulation.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.947-955
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• 2017

A competing risk analysis has been applied when subjects experience more than one type of end points. Geskus (2011) showed three types of estimators of CIF are equivalent under left truncated and right censored data. We extend his approach to an interval censored competing risk data by using a modified risk set and evaluate their performance under several sample sizes. These estimators show very similar results. We also suggest a test statistic combining Sun's test for interval censored data and Gray's test for right censored data. The test sizes and powers are compared under several cases. As a real data application, the suggested method is applied a data where the feasibility of the vaccine to HIV was assessed in the injecting drug uses.

• International Journal of Reliability and Applications
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• v.4 no.4
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• pp.171-181
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• 2003

This paper proposes a U-test statistic for the problem of testing that a life distribution is exponential against the alternative that it is harmonic new better (worse) than used in expectation upper tail HNBUET (HNWUET), but not exponential on complete data. Selected critical values are tabulated for sample sizes n =5(1)60. The asymptotic normality of the statistic is proved and a comparison is made of the asymptotic efficiency between the statistic and other statistics. The power of the test is studied by simulation. A test for HNBUET in the case of randomly right-censored data is also considered. An application of the proposed test statistic in medical sciences is given.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.543-557
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• 2006

This paper is concerned with the applicability of the chi-square approximation to the six disparity statistics: the Pearson chi-square, the generalized likelihood ratio, the power divergence, the blended weight chi-square, the blended weight Hellinger distance, and the negative exponential disparity statistic. Three dimensional contingency tables of small and moderate sample sizes are generated to be fitted to all possible hierarchical log-linear models: the completely independent model, the conditionally independent model, the partial association models, and the model with one variable independent of the other two. For models with direct solutions of expected cell counts, point estimates and confidence intervals of the 90 and 95 percentage points of six statistics are explored. For model without direct solutions, the empirical significant levels and the empirical powers of six statistics to test the significance of the three factor interaction are computed and compared.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.307-314
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• 2021

We showed that any missing mechanism is reproduced by EMAR or MNAR with equal fit for observed likelihood if there are non-negative solutions of maximum likelihood equations. This is a generalization of Molenberghs et al. (2008) and Jeon et al. (2019). Nonetheless, as MCAR becomes a nested model of MNAR, a natural question is whether or not MNAR and MCAR are testable by using the well-known three statistics, LR (Likelihood ratio), Wald, and Score test statistics. Through simulation studies, we compared these three statistics. We investigated to what extent the boundary solution affect tesing MCAR against MNAR, which is the only testable pair of missing mechanisms based on observed likelihood. We showed that all three statistics are useful as long as the boundary proximity is far from 1.

• Journal of Integrative Natural Science
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• v.5 no.4
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• pp.241-245
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• 2012

Categorical data collected based on complex sample design is not proper for the standard Pearson multinomial-based chi-squared test because the observations are not independent and identically distributed. This study investigates effects of bias of point estimator of population proportion and its variance estimator to the standard Pearson chi-squared test statistics when the sample is collected based on complex sampling scheme. This study examines the effect under two population homogeneity test. The standard Pearson test statistic can be partitioned into two parts; the first part is the weighted sum of ${\chi}^2_1$ with eigenvalues of design matrix as their weights, and the additional second part which is added due to the biases of the point estimator and its variance estimator. Our empirical analysis shows that even though the bias of point estimator is small, Pearson test statistic is very much inflated due to underestimate the variance of point estimator. In the connection of design-based variance estimator and its design matrix, the bigger the average of eigenvalues of design matrix is, the larger relative size of which the first component part to Pearson test statistic is taking.