• Title/Summary/Keyword: asymptotic variance

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Nonresponse Adjusted Raking Ratio Estimation

  • Park, Mingue
    • Communications for Statistical Applications and Methods
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    • v.22 no.6
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    • pp.655-664
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    • 2015
  • A nonresponse adjusted raking ratio estimator that consists of weighting adjustment using estimated response probability and raking procedure is often used to reduce the nonresponse bias and keep the calibration property of the estimator. We investigated asymptotic properties of nonresponse adjusted raking ratio estimator and proposed a variance estimator. A simulation study is used to examine the performance of suggested estimators.

Estimation of Mean Residual Life Function for a Coherent System (코히어런트 시스템에서 평균잔여수명함수(平均殘餘壽命函數)의 추정(推定))

  • Park, Byung-Gu
    • Journal of the Korean Data and Information Science Society
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    • v.4
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    • pp.97-107
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    • 1993
  • In this paper we propose a nonparametric estimator of the men residual life function (MRLF) on a coherent system under the condition that the component lifetimes are censored by system lifetime. It is shown that the proposed estimator, considered as a function of age t, converges weakly to a Gaussian process on a fixed interval. A consistent estimator of asymptotic variance of the proposed estimator is also given.

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Optimal Plan of Partially Accelerated Life Tests under Type I Censoring

  • Moon, Gyoung-Ae
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.2
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    • pp.87-94
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    • 1994
  • In this paper, we consider optimum plan to determine stress change times under the three-step stress PALTs, assuming that each test units follows an exponential distribution. The tampered random variable(TRV) model for the three-step stress PALTs setup are introduced, and maximum likelihood estimators(MLEs) of the failure rate and the acceleration factors are obtained. The change times to minimize the generalized asymptotic variance(GAVR) of MLEs of the failure rate and the acceleration factors are proposed for the three-step stress PALTs.

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Rate of Convergence of Empirical Distributions and Quantiles in Linear Processes with Applications to Trimmed Mean

  • Lee, Sangyeol
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.435-441
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    • 1999
  • A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.

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A Modified Definition on the Process Capability Index Cpk Based on Median

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.527-535
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    • 2011
  • This study proposes a modified definition about $C_{pk}$ based on median as the centering parameter in order to more easily control the process since the mean does not represent any quantile of the asymmetric process distribution. Then we consider an estimate and derive the asymptotic normality for the estimate of the modified $C_{pk}$. In addition, we provide an example with asymmetric distributions and discuss the estimation for the limiting variance that are followed by some concluding remarks.

The Limit Distribution of a Modified W-Test Statistic for Exponentiality

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.473-481
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    • 2001
  • Shapiro and Wilk (1972) developed a test for exponentiality with origin and scale unknown. The procedure consists of comparing the generalized least squares estimate of scale with the estimate of scale given by the sample variance. However the test statistic is inconsistent. Kim(2001) proposed a modified Shapiro-Wilk's test statistic based on the ratio of tow asymptotically efficient estimates of scale. In this paper, we study the asymptotic behavior of the statistic using the approximation of the quantile process by a sequence of Brownian bridges and represent the limit null distribution as an integral of a Brownian bridge.

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Heteroscedasticity of Random Effects in Crossover Design

  • Ahn, Chul-H.
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.79-83
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    • 2002
  • A phase III clinical trial of a new drug for neutropenia induced by chemotherapy is presented and consider adding random effects in crossover design which was used in the clinical study. The diagnostics for its heteroscedasticity based on score statistic is derived for detecting homoscedasticity of errors in crossover design. A small simulation study is peformed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

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Optimal Plan for Fully Accelerated Life Tests with Three-Step Stress Under Type I Censoring

  • Moon, Kyoung-Ae;Shin, Im-Hee
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.295-299
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    • 1996
  • In this paper, optimal change times are determined for fully three-step stress accelerated life tests, which minimize the asymptotic variance for maximum likelihood estimator of logarithm of the failure rate at the usual condition and exponential distribution is given for life time data.

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The Asymptotic Unbiasedness of $S^2$ in the Linear Regression Model with Dependent Errors

  • Lee, Sang-Yeol;Kim, Young-Won
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.235-241
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    • 1996
  • The ordinary least squares estimator of the disturbance variance in the linear regression model with stationary errors is shown to be asymptotically unbiased when the error process has a spectral density bounded from the above and away from zero. Such error processes cover a broad class of stationary processes, including ARMA processes.

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Sequential Estimation of variable width confidence interval for the mean

  • Kim, Sung Lai
    • Journal of the Chungcheong Mathematical Society
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    • v.14 no.2
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    • pp.47-54
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    • 2001
  • Let {Xn, n = 1,2,${\cdots}$} be i.i.d. random variables with the only unknown parameters mean ${\mu}$ and variance a ${\sigma}^2$. We consider a sequential confidence interval C1 for the mean with coverage probability 1-${\alpha}$ and expected length of confidence interval $E_{\theta}$(Length of CI)/${\mid}{\mu}{\mid}{\leq}k$ (k : constant) and give some asymptotic properties of the stopping time in various limiting situations.

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