• Communications for Statistical Applications and Methods
• /
• 제9권2호
• /
• pp.533-542
• /
• 2002

In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.

• Communications for Statistical Applications and Methods
• /
• 제18권6호
• /
• pp.751-759
• /
• 2011

The method of generalized estimating equations(GEE) is widely used in the analysis of a correlated dataset that consists of repeatedly observed responses within subjects. The GEE uses a quasi-likelihood equations to find the parameter estimates without assuming a specific distribution for the correlated responses. In this paper we study the importance of specifying the working correlation structure appropriately in fitting GEE for correlated counts data. We investigate the empirical coverages of confidence intervals for the regression coefficients according to four kinds of working correlations where one structure should be specified by the users. The confidence intervals are computed based on the asymptotic normality and the sandwich variance estimator.

• Communications for Statistical Applications and Methods
• /
• 제21권2호
• /
• pp.115-124
• /
• 2014

In this paper we derive a Berry-Esseen type bound for the kernel density estimator of a random left truncated model, in which each datum (Y) is randomly left truncated and is sampled if $Y{\geq}T$, where T is the truncation random variable with an unknown distribution. This unknown distribution is estimated with the Lynden-Bell estimator. In particular the normal approximation rate, by choice of the bandwidth, is shown to be close to $n^{-1/6}$ modulo logarithmic term. We have also investigated this normal approximation rate via a simulation study.

• Communications for Statistical Applications and Methods
• /
• 제27권5호
• /
• pp.511-521
• /
• 2020

In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

• Journal of the Korean Statistical Society
• /
• 제27권3호
• /
• pp.369-383
• /
• 1998

This paper deals with a robust regression estimator. We propose an efficient one-step GM-estimator, which has a bounded influence function and a high breakdown point. The main idea of this paper is to use the Mallows-type weights which depend on both the predictor variables and the residuals from a high breakdown initial estimator. The proposed weighting scheme severely downweights the bad leverage points and slightly downweights the good leverage points. Under some regularity conditions, we compute the finite-sample breakdown point and prove the asymptotic normality. Some simulation results and a numerical example are also presented.

• Journal of the Korean Data and Information Science Society
• /
• 제12권2호
• /
• pp.125-143
• /
• 2001

We, in this paper, propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation. Two examples are illustrated for our results.

• Journal of the Korean Data and Information Science Society
• /
• 제10권1호
• /
• pp.37-45
• /
• 1999

본 논문에서는 Marshall-Olkin의 이변량 지수모형을 따르는 두 부품의 수명들이 이변량 임의 중단된 자료로 관찰되는 경우를 생각한다. 이 경우 모수와 시스템 신뢰도에 대한 최우추정량을 구하고 근사적 정규성을 이용하여 두 부품의 수명에 대한 동일성 및 독립성 검정법을 제안한다. 그리고 모의실험을 통하여 제안된 추정량들과 검정법들의 유의확률을 계산한다.

• International Journal of Reliability and Applications
• /
• 제5권4호
• /
• pp.105-113
• /
• 2004

The exponential better (worse) than used EBU (EWU) class of life distributions is considered. A moment inequality is derived for EBU (EWU) distributions which demonstrate that if the mean life is finite, then all moments exist. Based on this inequality, a new test statistic for testing exponentiality against EBU (EWU) is introduced. It is shown that the proposed test is simple, enjoys good power and has high relative efficiency for some commonly used alternatives. Critical values are tabulated for sample sizes n = 5(1)40. A set of real data is used as a practical application of the proposed test in the medical science.

• International Journal of Reliability and Applications
• /
• 제3권1호
• /
• pp.17-23
• /
• 2002

The class of “new better than used of a specified age” is a large and practical class of life distributions. Its properties, applicability, and testing was discussed by Hollander, Park and Proschan (1986). Their test, while remaining the yardstick for this class, suffers from weak efficiency and weak power, especially for specified ages below the average age. Thus, it is beneficial to have an alternative testing procedure that would work better for early ages and still work well for later ages. This is exactly the subject of the current note. The test developed here is also simpler than that of Hollander, et. al. (1986).

• 대한전기학회논문지:시스템및제어부문D
• /
• 제54권7호
• /
• pp.423-427
• /
• 2005

In this paper, we proposed a new ARMA model identification which estimate the parameters to make the current prediction error uncorrelated with the past one. As good properties of the proposed method, we show the uniqueness, consistency of the estimate and asymptotic normality of the estimation error. Via simulation results, we show that the proposed method give good estimates for various systems which have different power spectrum. Moreover, the estimation of gyroscope random errors shows that the proposed method is applicable to the real data.