• 제목/요약/키워드: nonparametric

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NONPARAMETRIC ESTIMATION OF THE VARIANCE FUNCTION WITH A CHANGE POINT

  • Kang Kee-Hoon;Huh Jib
    • Journal of the Korean Statistical Society
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    • 제35권1호
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    • pp.1-23
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    • 2006
  • In this paper we consider an estimation of the discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of the change point in the variance function and then construct an estimator of the entire variance function. We examine the rates of convergence of these estimators and give results for their asymptotics. Numerical work reveals that using the proposed change point analysis in the variance function estimation is quite effective.

Nonparametric Granger Causality Test

  • Jeong, Ki-ho;Nishiyama, Yoshihiko
    • Journal of the Korean Data and Information Science Society
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    • 제18권1호
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    • pp.195-210
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    • 2007
  • This paper develops a consistent nonparametric test for Granger causality in the context of strong-mixing process, which covers a large class of stationary processes including ARMA and ARCH models. The previously proposed tests require absolute regularity ($\beta$-mixing) more stringent than the strong-mixing condition. We prove the consistency of the test under a high level assumption on the approximation error of U statistic by its projection. Due to the sample splitting, the test statistic we propose is asymptotically normally distributed under the null.

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On statistical properties of some dierence-based error variance estimators in nonparametric regression with a finite sample

  • Park, Chun-Gun
    • Journal of the Korean Data and Information Science Society
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    • 제22권3호
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    • pp.575-587
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    • 2011
  • We investigate some statistical properties of several dierence-based error variance estimators in nonparametric regression model. Most of existing dierence-based methods are developed under asymptotical properties. Our focus is on the exact form of mean and variance for the lag-k dierence-based estimator and the second-order dierence-based estimator in a nite sample size. Our approach can be extended to Tong's estimator (2005) and be helpful to obtain optimal k.

Some nonparametric test procedure for the multi-sample case

  • Park, Hyo-Il;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • 제20권1호
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    • pp.237-250
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    • 2009
  • We consider a nonparametric test procedure for the multi-sample problem with grouped data. We construct the test statistics based on the scores obtained from the likelihood ratio principle and derive the limiting distribution under the null hypothesis. Also we illustrate our procedure with an example and obtain the asymptotic properties under the Pitman translation alternatives. Also we discuss some concluding remarks. Finally we derive the covariance between components in the Appendix.

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On the Study for the Simultaneous Test

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • 제20권4호
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    • pp.241-246
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    • 2013
  • In this study, we propose a nonparametric simultaneous test procedure for the location translation and scale parameters. We consider the Wilcoxon rank sum test for the location translation parameter and the Mood test for the scale parameter with the quadratic and maximal types of combining functions. Then we derive the limiting null distributions of the combining functions. We illustrate our procedure with an example and compare efficiency by obtaining the empirical powers through a simulation study. Finally, we discuss some interesting features related to the nonparametric simultaneous tests.

Nonparametric Estimation of Mean Residual Life by Partial Moment Approximation under Proportional Hazard Model

  • Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • 제15권4호
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    • pp.965-971
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    • 2004
  • In this paper we consider several nonparametric estimators for the mean residual life by using the partial moment approximation under the proportional hazard model. Also we compare the magnitude of mean square error of the proposed nonparametric estimators for mean residual life under the proportional hazard model.

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NONPARAMETRIC ONE-SIDED TESTS FOR MULTIVARIATE AND RIGHT CENSORED DATA

  • Park, Hyo-Il;Na, Jong-Hwa
    • 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.

Nonparametric Test for Multivariate Location Translation Alternatives

  • Na, Jong-Hwa
    • 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.

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Multivariate Test based on the Multiple Testing Approach

  • Hong, Seung-Man;Park, Hyo-Il
    • 응용통계연구
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    • 제25권5호
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    • pp.821-827
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    • 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.

Nonparametric Estimation using Regression Quantiles in a Regression Model

  • Han, Sang-Moon;Jung, Byoung-Cheol
    • 응용통계연구
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    • 제25권5호
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    • pp.793-802
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    • 2012
  • One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.