• Journal of the Korean Statistical Society
• /
• v.28 no.1
• /
• pp.45-55
• /
• 1999

Knowing the number of unit roots is important in the analysis of k-dimensional multivariate autoregressive process. In this paper we suggest simple multiple unit roots test statistics based on least squares estimator for the multivariate AR(1) process in which some eigenvalues are one and the rest are less than one in magnitude. The empirical distributions are tabulated for suggested test statistics. We have small Monte-Calro studies to compare the powers of the test statistics suggested by Johansen(1988) and in this paper.

• The Korean Journal of Applied Statistics
• /
• v.25 no.5
• /
• pp.821-827
• /
• 2012

In this study, we propose a new nonparametric test procedure for the multivariate data. In order to accommodate the generalized alternatives for the multivariate case, we construct test statistics via-values with some useful combining functions. Then we illustrate our procedure with an example and compare efficiency among the combining functions through a simulation study. Finally we discuss some interesting features related with the new nonparametric test as concluding remarks.

• International Journal of Reliability and Applications
• /
• v.8 no.1
• /
• pp.41-51
• /
• 2007

In this paper, we use the moments of order statistics derived by Lieblein (1955) to develop the correlation goodness-of-fit test for the Rayleigh distribution. In such we simulate the percentage points of the test statistics for the one-parameter and two-parameter cases. In addition, we calculate the power of the proposed tests based on some alterative distributions. Finally, we apply the procedures developed in the paper to some real data.

• Journal of the military operations research society of Korea
• /
• v.27 no.2
• /
• pp.124-133
• /
• 2001

The purpose of this study is investigate the differences among parametric and nonparametric test statistics for the tree alternative hypothesis in the randomized block design. As the results, it was found that there was no large differences among parametric and nonparametric test statistics in power when the block sizes were larger, and Hollander's statistic had better power than other nonparametric test statistics. It is recommended that Hollander's test statistic is more useful method when we have no information about the distribution of population.

• International Journal of Reliability and Applications
• /
• v.16 no.2
• /
• pp.113-122
• /
• 2015

In this paper, we introduce U-statistics approach to generalized Hollander-Proschan test for new better than used (NBUE) alternative. We prove, the proposed test is equivalent to test was introduced by Anis and Mitra (2011) and includes test was introduced by Hollander Proschan (1975). Also, the asymptotic properties are studied. The powers of our test are estimated. The Pitman asymptotic efficiencies of proposed test are also calculated. Finally, the test is applied to some real data.

• Communications for Statistical Applications and Methods
• /
• v.6 no.3
• /
• pp.909-918
• /
• 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
• /
• v.7 no.3
• /
• pp.789-798
• /
• 2000

The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

• Journal of the Korean Statistical Society
• /
• v.29 no.4
• /
• pp.423-433
• /
• 2000

In this paper, we consider applying the bootstrap method to the median test procedures for right censored data. For doing this, we show that the median test statistics can be represented by the differences of two sampler medians. Then we review to the re-sampling methods for censored dta and propose the test procedures under the location translation assumption and Behrens-Fisher problem. Also we compare our procedures with other re-sampling method, which is so-called permutation test through an example. Finally we show the validity of bootstrap median test procedure in the appendix.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.447-456
• /
• 2000

In this paper, we considered three methods for outlier identification sample surveys. First, we studied method of handling and adjusting outliers in normal population. Second, we studied existing methods using mean, maximum and minimum and proposed a test using of median which well reflects characteristic of data regardless of sampling distribution. Finally, we showed our test using median works better than Dixon and mean test through simulation.

• Communications for Statistical Applications and Methods
• /
• v.8 no.3
• /
• pp.851-858
• /
• 2001

Using the normalized sample Lorenz curve which is introduced by Kang and Cho (2001), we propose the test statistics for testing of normality that is very important test in statistical analysis and compare the proposed test with the other tests in terms of the power of test through by Monte Carlo method. The proposed test is more power than the other tests except some cases