• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.909-918
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• 1999

Arizono and Ohta(1989) studied goodness of fit test of normality using the entropy estimator proposed by Vasicek (1976) Recently van Es(1992) and Correa(1995) proposed an estimator of entropy. In this paper we propose goodness of fit test statistics for normality based on Vasicek ven Es and Correa. And we compare the power of the proposed test statistics with Kolmogorov-Smirnov Kuiper Cramer von Mises Watson Anderson-Darling and Finkelstein and Schefer statistics.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.125-134
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• 2014

Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.303-311
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• 2003

We consider the problem of testing cell probabilities in sparse multinomial data. Aerts, et al.(2000) presented $T_1=\sum\limits_{i=1}^k(\hat{p}_i-p_i)^2$ as a test statistic with the local polynomial estimator $(\hat{p}_i$, and showed its asymptotic distribution. When there are cell probabilities with relatively much different sizes, the same contribution of the difference between the estimator and the hypothetical probability at each cell in their test statistic would not be proper to measure the total goodness-of-fit. We consider a Pearson type of goodness-of-fit test statistic, $T=\sum\limits_{i=1}^k(\hat{p}_i-p_i)^2/p_i$ instead, and show it follows an asymptotic normal distribution.

• Communications for Statistical Applications and Methods
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• 제3권3호
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• pp.39-46
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• 1996

Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. In this paper we compare power of goodness-of-fit test statistics for testing the (null)parametric model versus the (alternative) nonparametric model.

• 응용통계연구
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• 제23권6호
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.

• 대한교통학회지
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• 제14권1호
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• pp.43-50
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• 1996

This paper is concerned with assessing goodness of fit of gravity models. The Chi-square test, or one of its asymptotic equivalents, is usually recommended for the purpose. A difficulty that frequently arises, particularly when working with urban travel data, is that the expected number of trips for most origin-destination(O-D) pairs are small. In order to test goodness of fit of gravity model, a simple approach, which depends on the number of O-D pairs and certain trip totals being large, is proposed in this paper. In addition, derivation of variance of Chi-square ratio is proposed to test the confidence interval of Chi-square ratio and application of its results with simulated data set is made to verify the usefulness of the results.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.37-46
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• 1996

계단충격가속수명시험에서 얻은 자료를 토대로 통계적 추론을 위해 가정하는 수명분포에 대한 적합도 검정을 Kolmogorov-Smirnov, Cramer-von Mises, Anderson-Darling과 같은 비모수적 검정통계량들을 이용한 검정절차를 제안하고, 각 통계량들을 검정력 측면에서 비교하고자 한다.

• Journal of the Korean Statistical Society
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• 제30권4호
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• International Journal of Reliability and Applications
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• 제10권1호
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• pp.59-62
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• 2009

We comment on a new testing procedure for testing exponentiality against different ageing classes. We show that the proposed test is inappropriate at least for two alternatives. We point out the subtle flaw in their argument.

• 한국보육지원학회지
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• 제13권1호
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• pp.43-63
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• 2017

Objective: The goal of this study was to clarify the differences in children's child care center adjustment depending on child-mother's goodness of fit. Methods: A total of 478 subjects, 239 dyads of 3 and 4 year old children and their mothers and 16 teachers participated in this study. The instruments used in this study were the DOTS-R, EAS Scale and PAQ. The collected data were analyzed using a t-test, Anova, and regression with the SPSS. Results: First, mother's demand was significantly different only with regard to the income level. Second, mother's temperament and mother's demand were positively correlated and the mother's demand was influenced by the mother's temperament. Third, mother's demand according to children's gender was indicated to differ significantly. Fourth, children's temperament and mother's demand were positively correlated and mother's demand was influenced by children's temperament. Finally, ego strength according to active and adoptive temperaments in child-mother's goodness of fit had significant differences. In addition, prosocial behavior according to regular temperament of child-mother's goodness of fit was indicated to have a significant difference. Conclusion/Implications: This study suggests that it is important for mothers to understand and appropriately demand the temperament of the children in the adaptation of the child care center.