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平方误差损失下若干联合单侧预检验估计量的抽样表现AI 解读

IN MANY AREAS OF SCIENCE, when drawing conclusions concerning a set of phenomena, individual or linear combinations of parameters are assumed to be nonnegative, nonpositive, or to lie between upper and lower bounds. Likewise, many functions are assumed to be monotonic, convex, or quasiconvex. Consequently, questions naturally arise as to the correctness of the assumptions and, within the context of statistical inference, how to evaluate the evidence against these assumptions…

T. A. Yancey, G. G. Judge, M. E. Bock, Wallace's Weak Mean Square Error Criterion for Testing Linear Restrictions in Regression: A Tighter Bound, Econometrica, Vol. 41, No. 6 (Nov., 1973), pp. 1203-1206

回归中预检验估计量的统计后果AI 解读

This study is concerned with deriving the properties of the preliminary test estimator for the general linear normal regression model, ascertaining the characteristics of the risk functions over the parameter space, and determining the conditions necessary for the risk of this estimator to exceed or be less than the conventional one under squared error loss. A test procedure and the problem of choosing an optimal level of significance for the test are discussed. Some…

Theil 混合回归估计量的若干有限样本结果AI 解读

Finite sample properties of Theil's mixed regression estimator and test statistic for checking the compatibility of prior and sample information, are studied via Monte Carlo sampling experiments.

Theil 混合回归估计量的若干有限样本结果AI 解读

Finite sample properties of Theil's mixed regression estimator and test statistic for checking the compatibility of prior and sample information, are studied via Monte Carlo sampling experiments.

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转移概率的极大似然与贝叶斯估计AI 解读

In this paper, maximum likelihood and Bayesian methods are presented for estimating transition probabilities when data in the form of aggregated proportions are available. The probability function for the observed proportions is assumed to have a multinomial distribution under the Lexis scheme. The multivariate beta distribution is used as the prior probability density function in formulating the Bayesian estimator. The results of some Monte Carlo experiments provide some…

回归分析中的不等式约束AI 解读

In order to combine prior and sample information in the estimation of regression coefficients, when the prior knowledge about the parameter space exists in the form of inequality constraints, the regression model is respecified as a quadratic programming problem. The sampling properties of the general restricted estimator are discussed and the inequality restricted formulation is extended to cover a set of regression equations. As an example of the applicability of the…