• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.166-176
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• 1994

Some rank score tests are proposed for testing the equality of all sampling distribution functions against ordered location-scale alternatives in k-sample problem. Under the null hypothesis and a contiguous sequence of ordered location-scale alternatives, the asymptotic properties of the proposed test statistics are investigated. Also, the asymptotic local powers are compared with each others. The results show that the proposed tests based on the Hettmansperger-Norton type statistic are more powerful than others for the general ordered location-scale alternatives. However, the Shiraishi's tests based on the sum of two Bartholomew's rank analogue statistics are robust.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.947-957
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• 2008

In this paper, we consider the c-sample location problem for ordered alternatives using median ranked ordering-set samples(MROSS). We propose the test statistic using the median of samples that have the same ranked order in each cycle of ranted ordering-set sample(ROSS). We obtain the asymptotic property of the proposed test statistic and Pitman efficiency with respect to other test statistic. In simulation study, our proposed test statistic has good powers for some underlying distributions we consider.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.563-573
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• 2000

In this thesis, we propose the test statistic for ordered alternatives on c-sample ranked set samples(RSS). The proposed test statistic JRSS is Jonckheere type statistic using the median of the i-th samples in each cycle. We obtained the asymptotic property of the proposed test statistic and the asymptotic relative efficiencies of the proposed test statistic with respect to J SRS which Jonckheere type statistic on simple random samples(SRS). From the simulation works, J RSS is superior to J SRS. We compared the empirical powers of J RSS with respect to U RSS on ranked set sample and U SRS on simple random sample using all samples, which are proposed by Kim, Kim and Lee(1999). The powers of J RSS are nearly the same values when entire sample size is large. J RSS is superior to U RSS. J RSS is simpler than U RSSon calculating process.

• Journal of the Korean Statistical Society
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• v.17 no.2
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• pp.61-80
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• 1988

For testing homogeneity of scale parameters aginst ordered alternatives, some nonparametric test statistics based on pairwise ranking method are proposed. The proposed tests are distribution-free. The asymptotic distributions of the proposed statistcs are also investigated. It is shown that the Pitman efficiencies of the proposed rank tests are the same as those of the corresponding two-sample rank tests in the scale problem. A small-sample Monte Carlo study is also performed. The results show that the proposed tests are robust and efficient.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.70-80
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• 1989

A nonparametric test for testing the parallelism of regression lines against ordered alternatives is proposed. The proposed test statistic is based on a linear combination of robust slope estimators. It is a modified version of the Adichie's test statistics based on scores. A snail-sample Monte Carlo study shows that the proposed test is compatible with the Adichie's test.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.195-204
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• 1996

Some rank tests for comparing r treatments against ordered alternatives are proposed when some of data are randomly cemsored, which are the weighted logrank tests based on pairwise-ranking scheme. The covariances of the proposed test statistics are explicitly obtained from the results of the counting process theory and the test procedures are illustrated by a numerical example. Simulation studies are also performed for comparing with the other well-known tests.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.669-682
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• 2001

In this paper a nonparametric test for the parallelism of k regression lines against ordered alternatives, when the independent variables are positive and all regression lines have a common intercept is proposed. The proposed test is based on a Jonckheere-type statistic applied to residuals. Under some conditions the proposed test statistic is asymptotically distribution-free. The small-sample powers of our test are compared with other tests by a Monte Carlo study. The simulation results show that the proposed test has significantly higher empirical powers than the other tests considered in this paper.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.565-579
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• 1997

A robust test is proposed for the problem of testing the parallelism of several regression lines against ordered alternatives. The proposed test statistic is based on a linear combination of one-step pairwise GM-estimators. We compare the performance of the proposed test with that of the other tests through a Monte Carlo simulation. The results of the simulation study show that the proposed test has stable levels, good empirical powers in various circumstances, and particularly higher empirical powers under the presence of extreme outliers or leverage points.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.479-486
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• 1999

In this paper we propose the test statistic for ordered alternatives on multiple ranked set samples. Since the proposed test statistic is Page type its asymptotic properties are easily obtained. From the simulation works we calculate the power of test statistic($P_{RSS}$) under the underlying distributions such as uniform normal double exponential logistic and Cauchy distribution.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.401-408
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• 1993

This paper suggests a nonparametric test for the parallelism of several regression lines against ordered alternatives. The test statistic is an extension of the Potthoff statistic. The asymptotic variance of the proposed statistic is estimated by Bootstrap method. The proposed test are compared with the Adichie's parametric and nonparametric tests.