• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.147-157
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• 2017

The test of transition probabilities in panel Markov chains are introduced. We deal with the hypotheses whether panel Markov chains have the same transition probabilities or not for all times. We suggest a LR test statistic for the test and its limit distribution is derived. We perform a simulation study to examine the limit distribution of test statistics when the number of the individuals are large.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.231-240
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• 2006

It is well understood that a paired comparison (paired t test) provides better precision than a group comparison (two-sample t test), when the pairing is effective (the variation within a pair is small). However, when the variation among the pairs is sufficiently small, the group comparison is likely to yield a better result. To get a statistical explanation of this, we examine the two methods through an analogy to one-way and two-way analysis of variance. We introduce a new measure, R statistic, which is the ratio of their confidence interval lengths, as a quantitative criterion for comparing the two methods. The distribution of the Rf statistic is described by t and F distribution functions. Through this characterization, we show that the paired comparison can be better than group comparison when the variation among the pairs is statistically significantly large.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.79-97
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• 2004

We propose a permutation approach to the classic Behrens-Fisher problem of comparing two means in the presence of unequal variances. It is motivated by the observation that a paired test is valid whether or not the variances are equal. Rather than using a single arbitrary pairing of the data, we average over all possible pairings. We do this in both a parametric and nonparametric setting. When the sample sizes are equal, the parametric version is equivalent to referral of the unpaired t-statistic to a t-table with half the usual degrees of freedom. The derivation provides an interesting representation of the unpaired t-statistic in terms of all possible pairwise t-statistics. The nonparametric version uses the same idea of considering all different pairings of data from the two groups, but applies it to a permutation test setting. Each pairing gives rise to a permutation distribution obtained by relabeling treatment and control within pairs. The totality of different mean differences across all possible pairings and relabelings forms the null distribution upon which the p-value is based. The conservatism of this procedure diminishes as the disparity in variances increases, disappearing completely when the ratio of the smaller to larger variance approaches 0. The nonparametric procedure behaves increasingly like a paired t-test as the sample sizes increase.

• 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.17 no.1
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• pp.89-103
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• 2004

If the given information is exact, though it is the little, we had better use it than not use in analysis. In this article, the problem of independence test in a contingency table is considered when two marginal distributions of a population are given exactly. For that case, a likelihood-ratio chi-squared test statistic and its Pearsonian type chi-squared test statistic are derived. By Monte Carlo Simulations the traditional chi-square tests and the derived tests are compared. And the related some testing problems are synthetically explained on a geometrical viewpoint.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.21-27
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• 1996

A testing procedure is considered to the problem of testing whether there exists a shift in scale at an unknown time point whem a fixed number of observations are drawn successively in time. A test statistic based on squared ranks test for equal variances is suggested and its aymptotic distrbution is dereived. Small sample power comparisons are performed.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.205-211
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• 2006

For a linear regression model, the necessary and sufficient condition for the asymptotic consistency of the outlier test statistic is known. An analogous condition for the nonlinear regression model is considered in this paper.

• Journal of the Korean Statistical Society
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• v.22 no.1
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• pp.125-132
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• 1993

Large sample test of homogeneity for a panel of more than two seasonal autoregressive processes is derived and its limiting distribution is found. Detailed results are shown for the important special case that the seasonal and nonseasonal autoregressive components are both of order one.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.37-41
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• 2014

Recently, a lot of research efforts has been directed toward spectrum sensing techniques exploiting the some characteristics of power spectrum. Among them, a sensing technique employing the maximum of power spectrum as a test statistic has appeared in the literature and its false alarm probability was also derived under the assumption that the test statistic follows the Gaussian distribution. This paper provides an exact form of the false alarm probability without using the assumption and compares it with the previous work.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1545-1550
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• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.