Add to ORKGABSTRACT We study estimators for the variance parameter u 2 of a stationary process. The estimators are based on weighted Cramer-van Mises statistics formed from the standardized time series of the process. Certain weightings yield estimators which are "first-order unbiased" for u 2 and which have low variance. We also show how the Cramer-von Mises estimators are related to the standardized time series area estimator; we use this relationship to establish additional estimators for u 2
In this dissertation, we consider analytic and numeric approaches to the solution of probabilistic s...
summary:We investigate estimators of the asymptotic variance $\sigma^2$ of a $d$–dimensional station...
In this study Gibbs sampling, a widely used simulation method, is ap-plied to the steady model, a si...
We study estimators for the variance parameter sigma(2) of a stationary process. The estimators are ...
We propose a new class of estimators for the asymptotic variance parameter of a stationary simulatio...
This thesis is concerned with simulation output analysis. In particular, we are inter- ested in est...
In a previous article, we studied a then-new class of standardized time series (STS) estimators for ...
This dissertation studies three classes of estimators for the asymptotic variance parameter of a sta...
This thesis describes and compares some of commonly used methods of variance estimation of various s...
In this thesis, we first present a variance estimation technique based on the standardized time seri...
A variety of estimators of the variance of the general regression (GREG) estimator of a mean have be...
This papers describes an estimator for a standard state-space model with coefficients generated by a...
This article considers inference about the variance of coefficients in time-varying parameter models...
[[abstract]]© 1993 INFORMS - Many commonly used estimators of the variance of the sample mean from a...
This article discusses estimates of variance for two-stage models. We present the sandwich estimate ...
In this dissertation, we consider analytic and numeric approaches to the solution of probabilistic s...
summary:We investigate estimators of the asymptotic variance $\sigma^2$ of a $d$–dimensional station...
In this study Gibbs sampling, a widely used simulation method, is ap-plied to the steady model, a si...
We study estimators for the variance parameter sigma(2) of a stationary process. The estimators are ...
We propose a new class of estimators for the asymptotic variance parameter of a stationary simulatio...
This thesis is concerned with simulation output analysis. In particular, we are inter- ested in est...
In a previous article, we studied a then-new class of standardized time series (STS) estimators for ...
This dissertation studies three classes of estimators for the asymptotic variance parameter of a sta...
This thesis describes and compares some of commonly used methods of variance estimation of various s...
In this thesis, we first present a variance estimation technique based on the standardized time seri...
A variety of estimators of the variance of the general regression (GREG) estimator of a mean have be...
This papers describes an estimator for a standard state-space model with coefficients generated by a...
This article considers inference about the variance of coefficients in time-varying parameter models...
[[abstract]]© 1993 INFORMS - Many commonly used estimators of the variance of the sample mean from a...
This article discusses estimates of variance for two-stage models. We present the sandwich estimate ...
In this dissertation, we consider analytic and numeric approaches to the solution of probabilistic s...
summary:We investigate estimators of the asymptotic variance $\sigma^2$ of a $d$–dimensional station...
In this study Gibbs sampling, a widely used simulation method, is ap-plied to the steady model, a si...