Showing papers by "T. W. Anderson published in 1986"
Book•
01 Jan 1986
TL;DR: The new statistical analysis of data is presented for the first time in a systematic fashion with real-time consequences for the quantity and quality of individual transactions.
Abstract: The new statistical analysis of data , The new statistical analysis of data , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
136 citations
TL;DR: In this article, maximum likelihood estimators are obtained for multivariate components of variance models under the condition that the effect covariance matrix is positive semidefinite with a maximum rank.
Abstract: Maximum likelihood estimators are obtained for multivariate components of variance models under the condition that the effect covariance matrix is positive semidefinite with a maximum rank. The rank of the estimator is random. The estimation procedure leads to a likelihood ratio test that the rank of the effect matrix is not greater than a given number against the alternative that the rank is not greater than a larger specified number. Linear structural relationship models and some factor analytic models can be put into this framework.
62 citations
TL;DR: In this article, a comparison of estimators is made on the basis of their mean squared errors and their concentrations of probability computed by means of asymptotic expansions of their distributions when the disturbance variance tends to zero and alternatively when the sample size increases indefinitely.
Abstract: Comparisons of estimators are made on the basis of their mean squared errors and their concentrations of probability computed by means of asymptotic expansions of their distributions when the disturbance variance tends to zero and alternatively when the sample size increases indefinitely. The estimators include k-class estimators (limited information maximum likelihood, two-stage least squares, and ordinary least squares) and linear combinations of them as well as modifications of the limited information maximum likelihood estimator and several Bayes' estimators. Many inequalities between the asymptotic mean squared errors and concentrations of probability are given. Among medianunbiasedestimators, the limited information maximum likelihood estimator dominates the median-unbiased fixed k-class estimator.
41 citations
01 Sep 1986
TL;DR: In this paper, two Bayesian approaches based on Kalman filter models are proposed for the analysis of nonhomogeneous autoregressive processes, which are special cases of the vector-valued autoregression processes considered by Anderson (1978) for analysis of panel survey data.
Abstract: : This paper considers nonhomogeneous autoregressive processes which are special cases of the vector-valued autoregressive processes considered by Anderson (1978) for the analysis of panel survey data. The authors point out that, for a nonhomogeneous autoregressive process of order higher than one, the least-squares estimates cannot be obtained unless repeated measurements are made on the time series. Presented are two Bayesian approaches based on Kalman filter models which alleviate the above difficulty and result in an alternative strategy for the analyses of nonhomogeneous autoregressive processes. In the first approach the notion of exchangeability plays a key role, whereas for the second approach, which results in an adaptive Kalman filter model, an approximation due to Lindley facilitates the necessary computations for inference.
1 citations