• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.357-363
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• 1998

In this paper we propose a nonparametric lack of fit test based on the bootstrap method for testing the null parametric linear model by using linear smoothers. Most of existing nonparametric test statistics are based on the residuals. Our test is based on the centered bootstrap residuals. Power performance of proposed bootstrap lack of fit test is investigated via Monte carlo simulation.

• Journal of the Korean Statistical Society
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• 제29권4호
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• pp.423-433
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• 2000

In this paper, we consider applying the bootstrap method to the median test procedures for right censored data. For doing this, we show that the median test statistics can be represented by the differences of two sampler medians. Then we review to the re-sampling methods for censored dta and propose the test procedures under the location translation assumption and Behrens-Fisher problem. Also we compare our procedures with other re-sampling method, which is so-called permutation test through an example. Finally we show the validity of bootstrap median test procedure in the appendix.

• Communications for Statistical Applications and Methods
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• 제14권2호
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• pp.443-457
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• 2007

This paper deals with the problem of testing the existence of change in mean and estimating the change-point using nonparametric bootstrap technique. A test statistic using Gombay and Horvath (1990)'s functional form is applied to derive a test statistic and nonparametric change-point estimator with bootstrapping idea. Achieved significance level of the test is calculated for the proposed test to show the evidence against the null hypothesis. MSE and percentiles of the bootstrap change-point estimators are given to show the distribution of the proposed estimator in simulation.

• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.367-382
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• 2017

We consider an infinite-order long-memory heterogeneous autoregressive (HAR) model, which is motivated by a long-memory property of realized volatilities (RVs), as an extension of the finite order HAR-RV model. We develop bootstrap tests for structural mean or variance changes in the infinite-order HAR model via stationary bootstrapping. A functional central limit theorem is proved for stationary bootstrap sample, which enables us to develop stationary bootstrap cumulative sum (CUSUM) tests: a bootstrap test for mean break and a bootstrap test for variance break. Consistencies of the bootstrap null distributions of the CUSUM tests are proved. Consistencies of the bootstrap CUSUM tests are also proved under alternative hypotheses of mean or variance changes. A Monte-Carlo simulation shows that stationary bootstrapping improves the sizes of existing tests.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.587-592
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• 2016

It is a long-standing issue to correctly determine the number of long-run relationships among time series processes. We revisit nonparametric test for cointegration rank and propose bootstrap refinements. Consistent with model-free nature of the tests, we make use of Cholesky factor bootstrap methods, which require weak conditions for data generating processes. Simulation studies show that the original Breitung's test have difficulty in obtaining the correct size due to dependence in cointegrated errors. Our proposed bootstrapped tests considerably mitigate size distortions and represent a complementary approach to other bootstrap refinements, including sieve methods.

• Communications for Statistical Applications and Methods
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• 제23권2호
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• pp.163-177
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• 2016

We consider a jump diffusion process for high-frequency financial asset data. We apply the stationary bootstrapping to construct a bootstrap test for jumps. First-order asymptotic validity is established for the stationary bootstrapping of the jump ratio test under the null hypothesis of no jump. Consistency of the stationary bootstrap test is proved under the alternative of jumps. A Monte-Carlo experiment shows the advantage of a stationary bootstrapping test over the test based on the normal asymptotic theory. The proposed bootstrap test is applied to construct continuous-jump decomposition of the daily realized variance of the KOSPI for the year 2008 of the world-wide financial crisis.

• Journal of the Korean Data and Information Science Society
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• 제9권2호
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• pp.263-273
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• 1998

In this paper, we consider some approximate testings for the reliability of the stress-strength model when the stress X and strength Y each depends linearly on some explanatory variables z and w, respectively. We construct a bootstrap procedure for testing for various values of the reliability and compare the power of the bootstrap test with the test based on Mann-Whitney type estimator by Park et.al.(1996) for small and moderate sample size.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.521-529
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• 2005

In this paper, we consider a bootstrap method to the 'row and column effects model' (RC model) to analyze a contingency table with ordered variables. We propose a bootstrap procedure for testing of independence, equality of intervals, and goodness of fit in the RC model. A real data example is included.

• 통합자연과학논문집
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• 제15권1호
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• pp.9-18
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• 2022

This research examines the power of bootstrap two-sample test, and compares it with the powers of two-sample t-test and Wilcoxon rank sum test, through simulation. For simulation work, a positively skewed and heavy tailed distribution was selected as a population distribution, the chi-square distributions with three degrees of freedom, χ²₃. For two independent samples, the fist sample was selected from χ²₃. The second sample was selected independently from the same χ²₃ as the first sample, and calculated d+ax for each sampled value x, a randomly selected value from χ²₃. The d in d+ax has from 0 to 5 by 0.5 interval, and the a has from 1.0 to 1.5 by 0.1 interval. The powers of three methods were evaluated for the sample sizes 10,20,30,40,50. The null hypothesis was the two population medians being equal for Bootstrap two-sample test and Wilcoxon rank sum test, and the two population means being equal for the two-sample t-test. The powers were obtained using r program language; wilcox.test() in r base package for Wilcoxon rank sum test, t.test() in r base package for the two-sample t-test, boot.two.bca() in r wBoot pacakge for the bootstrap two-sample test. Simulation results show that the power of Wilcoxon rank sum test is the best for all 330 (n,a,d) combinations and the power of two-sample t-test comes next, and the power of bootstrap two-sample comes last. As the results, it can be recommended to use the classic inference methods if there are widely accepted and used methods, in terms of time, costs, sometimes power.

• 한국심리학회지:법
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• 제11권1호
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• pp.21-36
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• 2020

P300 숨긴정보검사에서는 조사대상자가 거짓을 말하고 있는지 판단하기 위하여 관련자극의 P300 진폭이 무관련자극의 P300 진폭보다 통계적으로 유의하게 더 큰지를 평가한다. 구체적인 통계적 방법으로 독립표본 t 검증 또는 부트스트랩 방법을 사용할 수 있다. Rosenfeld와 Soskins, Bosh, Ryan(2004)은 "개인 내에서 관련자극과 무관련자극의 P300 평균을 비교하는데 사용하기에는 t 검증이 너무 둔감하다."면서 부트스트랩 방법을 사용하였다. 본 연구의 목적은 P300 숨긴정보검사에서 t 검증의 검증력이 부트스트랩 방법보다 더 낮은지 평가하는 것이다. 이를 위하여 39명의 실험참가자로부터 측정한 뇌파자료를 이용하여 Monte Carlo 연구를 수행하였다. 연구결과, t 검증과 백분위를 이용한 부트스트랩 방법의 1 종 오류율은 서로 비슷하였으며, 백분위를 이용한 부트스트랩 방법의 검증력이 t 검증의 검증력보다 약간 더 높았다. 두 검증 방법의 1 종 오류율은 모두 유의수준보다 낮은 값을 보였으며, 검증력은 이론적인 t 검증의 검증력보다 약간 낮은 값을 보였다. 반면에 표준오차를 이용한 부트스트랩 방법의 1 종 오류율과 검증력은 이론적인 t 검증의 1 종 오류율 및 검증력과 비슷한 값을 보였으며, t 검증의 검증력보다 실험조건에 따라 .012 ~ .081 더 높았다.