• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.637-642
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• 2013

In this paper, we consider the maximum entropy test in in nite order autoregressiv models. Its asymptotic distribution is derived under the null hypothesis. A bootstrap version of the test is discussed and its performance is evaluated through Monte Carlo simulations.

• Journal of the Korean Statistical Society
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• v.30 no.4
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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.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.799-809
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• 2000

In this paper we propose a nonparametric one sided test for location parameters in p-variate(p$\geq$2) location translation model. The exact null distributions of test statistics are calculated by permutation principle in the case of relatively small sample sizes and the asymptotic distributions are also considered. The powers of various tests are compared through computer simulation and thep-values with real data are also suggested through example.

• Journal of the Korean Statistical Society
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• v.7 no.1
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• pp.17-26
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• 1978

For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.677-683
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• 1997

For an AR(1) model with intercept $y_t=\mu+\rho{y_{t-1}}+e_t$, a test for random walk hypothesis $H_0:(\mu, \rho)=(0, 1)$is proposed, which is based on the symmetric estimator. In the vicinity of the null, the test in shown to be more powerful than the test of Dickey and Fuller(1981) based on the ordinary least squares estimator.

• The Pure and Applied Mathematics
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• v.4 no.1
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• pp.7-18
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• 1997

Consider an $r\;\times\;c$ contingency table under the full multinomial model in which each classification is ordered. The problem is to test the null hypothesis of independence. A number of tests have been proposed for this problem. In this article we show that all of these tests can be improved on in some sense for most cases. In fact the preceding tests sometimes are inadmissible in a strict sense. Furthermore, we show by example that in some cases improved tests can yield substantially improved power functions.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.189-195
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• 1998

In this paper, we are concerned with the problem of testing the randomness of the coefficients in a first order autoregressive model. A consistent test based on prediction error is suggested. It is shown that under the null hypothesis, the test statistic is asymptotically normal.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.67-77
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• 1999

For a orientation-shift model supported on the unit sphere, Euler angles are the conventional measure to parametrize orientation-shifts. The essential role which is played by rotationally symmetry of an underlying distribution is reviewed. In this paper we propose the inference procedure based on Euler angles for the rotationally symmetric spherical distribution. The likelihood ratio test(LRT) based on the Euler angles is worked out. The asymptotic distribution of the test under the null hypotheses and certain contiguous alternatives is obtained.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.125-143
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• 1993

The primary objective of the paper is to review the development of approximations of the null distribution of a scan statistic and to show how these approximations were improved. Let $X_1, \cdots, X_N$ be a sequence of independent uniform random variables on an interval (0, t]. A can statistic is defined to be the maximum number of observations in a subinterval of length t $\leq$ T, when we continuously (or discretely) move the subinterval from 0 to T. A scan statistic is used to test whether certain events occur in a cluster aganist a null hypothesis of the uniformity. It is difficult to calculate the exact null distribution of a scan statistic. Several authors have suggested approximations of the null distribution of a scan statistic since Naus(1966). We conceive that a scan statistic can be used for detecting a "hot region" is defined to be a region at which the frequencies of mutations are relatively high. A "hot region" may be regarded as a generalized version of a hot spot. We leave it for a further study the concrete formulation of deteciton a "hot region" in a mutational spectrum.uot; in a mutational spectrum.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.69-73
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• 2012

Cancer is a complex disease and the genetic susceptibility to it could be an outcome of the inherited difference in the capacity of xenobiotic metabolizing enzymes. Glutathione-S-transferases (GSTs) are phase II metabolizing enzymes whose various genotypes have been associated with increased risk of different types of cancer. Null mutations caused by the deletion of the entire gene result in the absence of the enzymatic activity and increase in the risk of developing cancer including chronic myeloid leukaemia (CML). In the present case-control study we evaluated the effect of null mutations in GSTM1 and GSTT1 genes on the risk of developing CML. The study included 75 CML patients (43 males and 32 females; age (mean ${\pm}$ S.D) $42.3{\pm}13.4$ years) and unrelated non-malignant controls (76 male and 48 females; age (mean ${\pm}$ S.D) $41.5{\pm}12.9$). The distribution of GSTM1 and GSTT1 genotypes in CML patients and controls was assessed by multiplex-PCR method. Logistic regression was used to assess the relationship between GSTM1 and GSTT1 genotypes and risk of CML. Chi-square test was used to evaluate the trend in modulating the risk to CML by one or more potential high risk genotype. Although GSTM1 null genotype frequency was higher in CML patients (41%) than in the controls (35%), it did not reached a statistical significance (OD = 1.32, 95% CI: 0.73-2.40; P value = 0.4295). The frequency of GSTT1 null genotypes was higher in the CML patients (36%) than in the controls (21%) and the difference was found to be statistically significant (OD = 2.12, 95% CI: 1.12-4.02; P value = 0.0308). This suggests that the presence of GSTT1genotype may have protective role against the CML. We found a statistically significant (OD = 3.09, 95% CI: 1.122-8.528; P value = 0.0472) interaction between the GSTM1 and GSTT1 null genotypes and thus individuals carrying null genotypes of both GSTM1 and GSTT1 genes are at elevated risk of CML.