• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.279-293
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• 2006

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the exponential distribution based on multiply Type-II censored samples. Then three type tests, including the modified Clamor-von Mises test, the modified Watson test and the modified Kolmogorov-Smirnov test are developed for the exponential distribution based on multiply Type-II censored samples by using the proposed estimators. For each test, Monte Carlo techniques are used to generate critical values. The powers of these tests are investigated under several alternative distributions.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.99-113
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• 2005

In this article, we propose a chi-squared test of spherical symmetry. The advantage of this test is that the test statistic and its asymptotic p-value are easy to compute. The limiting distribution of the test statistic is derived under spherical symmetry and its accuracy, in finite samples, is studied via simulation. Also, a simulation study is conducted in which the power of our test is compared with those of other tests for spherical symmetry in various alternative distributions. Finally, an illustrative example of application to a real data is provided.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.201-215
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• 2000

The classical method for regression analysis is the least squares method. However, if the data contain significant outliers, the least squares estimator can be broken down by outliers. To remedy this problem, the robust methods are important complement to the least squares method. Robust methods down weighs or completely ignore the outliers. This is not always best because the outliers can contain some very important information about the population. If they can be detected, the outliers can be further inspected and appropriate action can be taken based on the results. In this paper, I propose a sequential outlier test to identify outliers. It is based on the nonrobust estimate and the robust estimate of scatter of a robust regression residuals and is applied in forward procedure, removing the most extreme data at each step, until the test fails to detect outliers. Unlike other forward procedures, the present one is unaffected by swamping or masking effects because the statistics is based on the robust regression residuals. I show the asymptotic distribution of the test statistics and apply the test to several real data and simulated data for the test to be shown to perform fairly well.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.381-393
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• 2005

As a promising technique for dimension reduction in regression analysis, Sliced Inverse Regression (SIR) and an associated chi-square test for dimensionality were introduced by Li (1991). However, Li's test needs assumption of Normality for predictors and found to be heavily dependent on the number of slices. We will provide a unified asymptotic test for determining the dimensionality of the SIR model which is based on the probabilistic principal component analysis and free of normality assumption on predictors. Illustrative results with simulated and real examples will also be provided.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.107-115
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• 2010

The newly revised bioequivalence guideline of Korea allows the add-on test since July 1, 2008 and some discussion from statistical point of view would be needed for a practical use. The statistical model of add-on test is introduced and its two stage testing procedures are discussed. Meaningful statistical points of the add-on test are delivered through an illustrated example.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.233-241
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• 2017

Interval censored data frequently occur in observation studies where the subject is followed periodically. In this paper, our interest is to suggest a test statistic to compare the CIF of two groups with interval censored failure time data in the presence of competing risks. Gray (1988) suggested a test statistic for right censored data that motivated a well-known Fine and Gray's subdistribution hazard model. A multiple imputation technique is adopted to adopt Gray's test statistic to interval censored data. The powers and sizes of the suggested method are investigated through diverse simulation schemes. The main merit of the suggested method is its simplicity to implement with existing software for right censored data. The method is illustrated by analyzing Bangkok's HIV cohort dataset.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.1-12
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• 1995

Let F be a life distribution with finite mean $\mu$ Then F is said to be in new better then worse than used in expectation (NBWUE(p)) class if $\varphi(u) {\geq} u$ for $0 {\leq}u{\leq}t_0$ and ${\varphi}(u) {\leq} u$ for $t_0< u {\leq} 1$ where ${\varphi}(u)$ is the scaled total-time-on-test transform and $p=F(t_0)$. We propose a testing procedure for $H_0$ : F is exponential against $H_1$ : NBWUE(p), and is not expontial, (or $H_1\;'$ : F is NWBUE (p), and is not exponential) using randomly censored data. Our procedure assumes kmowledge of the proportion p of the population that fail at or before the change-point $\t_0$. Know ledge of $\t_0$ itself is not assumed. The asymptotic normality of the test statistic is established and a Monte Carlo experiment is performed to investigate the speed of convergence of the test statistic to normality. The power of our test is also studied.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.521-529
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• 2013

The acceptance of the test of the homogeneity for panel time series models allows for the pooling of the series to achieve parsimony. In this paper, we introduce a panel bilinear time series model as well as derive the stationary condition and the limiting distribution of the test statistic of the homogeneity test for the model. For the applications study, we use Korea Mumps data from January 2001 to December 2008. Finally, we perform test of homogeneity for the panel data with 8 independent bilinear time series.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.307-315
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• 2014

An exact distribution of the test statistic to test for multiple outlier candidates does not generally exist; therefore, tests of individual outliers (or tests using simulated critical-values) are usually conducted instead of testing for groups of outliers. This article is on procedures to test outlying observations. We suggest a method that can be applied to arbitrary observations or multiple outlier candidates detected by an outlier detecting method. A Monte Carlo study performance is used to compare the proposed method with others.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1067-1080
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• 2010

A number of methods have been developed to determine sample sizes in clinical trial, and most clinical trial organizations determine sample sizes based on the methods. In contrast, determining sufficient sample sizes needed for experiments using microarray chips is unsatisfactory and not widely in use. In this paper, our objective is to provide a guideline in determining sample sizes, utilizing reproducibility of real microarray data. In the reproducibility comparison, five methods for discovering differential expression are used: Fold change, Two-sample t-test, Wilcoxon rank-sum test, SAM, and LPE. In order to standardize gene expression values, both MAS5 and RMA methods are considered. According to the number of repetitions, the upper 20 and 100 gene accordances are also compared. In determining sample sizes, more realistic information can be added to the existing method because of our proposed approach.