• Journal of the Korean Statistical Society
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• 제32권4호
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• pp.373-384
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• 2003

In this paper, we formulate multivariate one-sided alternatives and propose a class of nonparametric tests for possibly right censored data. We obtain the asymptotic tail probability (or p-value) by showing that our proposed test statistics have asymptotically multivariate normal distributions. Also, we illustrate our procedure with an example and compare it with other procedures in terms of empirical powers for the bivariate case. Finally, we discuss some properties of our test.

• 응용통계연구
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• 제4권1호
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• pp.33-45
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• 1991

변화시점 모형은 지금까지 한 시점에서 단 한 개의 관측자료를 갖는 모형만 생각해 왔다. 이러한 모형을 확장시켜 각 시점에 한 개 이상의 관측자료를 갖는 변화시점 모형을 생각한다. 이러한 모형에서 비모수적인 단측 그리고 양측 검정법을 찾았다. 검정 통계량은 지금까지 소개된 검정 통계량 형태를 확장시킨 형태이고 이들의 귀무가설 분포를 구하여 보았다. 또한 Monte Carlo연구를 통해 이들의 검정력을 비교해 보았다.

• Communications for Statistical Applications and Methods
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• 제7권3호
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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.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.709-717
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• 2008

The difference of two one-sided kernel estimators is usually used to detect the location of the discontinuity points of regression function. The large absolute value of the statistic imply discontinuity of regression function, so we may use the difference of two one-sided kernel estimators as the test statistic for testing null hypothesis of a smooth regression function. The problem is, however, we only know the asymptotic distribution of the test statistic under $H_0$ and we hardly expect the good performance of test if we rely solely on the asymptotic distribution for determining the critical points. In this paper, we show that if we adjust the bias of test statistic properly, the asymptotic rules hold for even small sample size situation.

• Journal of the Korean Statistical Society
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• 제19권2호
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• pp.128-138
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• 1990

In this paper we study the properties of nonparametric tests for testing the null hypothesis of no changes against one sided and two sideds alternatives in scale parameter at unknown point. We first propose two types of nonparametric tests based on linear rank statistics and rank-like statistics, respectively. For these statistics, we drive the asymptotic distributions under the null and contiguous alternatives. The main theoreticla tools used for derivation are the stochastic process representation of the test staistic and the Brownian bridge approximation. We evaluate the Pitman efficiencies of the test for the contiguous alternatives, and also compute empirical power by Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.669-678
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• 2007

An algorithm to detect the number of discontinuity points of the variance function in regression model is proposed. The proposed algorithm is based on the left and right one-sided kernel estimators of the second moment function and test statistics of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size. The finite sample performance is illustrated by simulated example.