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非参数变量选择：EARTH算法AI 解读

We consider regression experiments involving a response variable Y and a large number of predictor variables X1, …, Xd, many of which may be irrelevant for the prediction of Y and thus must be removed before Y can be predicted from the X’s. We consider two procedures that select variables by using importance scores that measure the strength of the relationship between predictor variables and a response and keep those variables whose importance scores exceed a threshold. In…

矩阵对数协方差模型AI 解读

A flexible method is introduced to model the structure of a covariance matrix C and study the dependence of the covariances on explanatory variables by observing that for any real symmetric matrix A, the matrix exponential transformation, C = exp (A), is a positive definite matrix. Because there is no constraint on the possible values of the upper triangular elements on A, any possible structure of interest can be imposed on them. The method presented here is not intended to…

两种基于多项分布的会计总体高估误差总额下界方法的性能比较AI 解读

Accurately estimating a lower bound on the total overstatement error in an accounting population is important in many audit decision situations. This article reports the results of a simulation study of three lower-bound estimation procedures based on a multinomial model with a dollar-unit sampling scheme. The ability of each procedure to attain a specified confidence level is assessed with respect to changes in error rate and random sampling method. The simulation study…

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贝叶斯边际推断AI 解读

A method is proposed for approximating the marginal posterior density of a continuous function of several unknown parameters, thus permitting inferences about any parameter of interest for nonlinear models when the sample size is finite. Possibly tedious numerical integrations are replaced by conditional maximizations, which are shown to be quite accurate in a number of special cases. There are similarities with the profile likelihood ideas originated by Kalbfleisch and…

贝叶斯边际推断AI 解读

A method is proposed for approximating the marginal posterior density of a continuous function of several unknown parameters, thus permitting inferences about any parameter of interest for nonlinear models when the sample size is finite. Possibly tedious numerical integrations are replaced by conditional maximizations, which are shown to be quite accurate in a number of special cases. There are similarities with the profile likelihood ideas originated by Kalbfleisch and…

存在干扰参数时假设显著性检验的广义 p 值AI 解读

This article examines some problems of significance testing for one-sided hypotheses of the form H 0 : θ ≤ θ 0 versus H 1 : θ > θ 0, where θ is the parameter of interest. In the usual setting, let x be the observed data and let T(X) be a test statistic such that the family of distributions of T(X) is stochastically increasing in θ. Define Cx as {X : T(X) — T(x) ≥ 0}. The p value is p(x) = sup θ≤θ0 Pr(X ∈ Cx | θ). In the presence of a nuisance parameter η, there may not exist…

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Clevenson–Zidek 型均值估计量稳健性的进一步研究AI 解读

Tsui (1984) showed that many Clevenson—Zidek-type Poisson means estimators are better than the usual estimator under the normalized squared error loss (1.1), even when the underlying distributions are negative binomial. This article shows that this dominance result is still true when the underlying distributions belong to a much larger class of distributions. This class includes all mixtures of Poisson distributions, and hence the negative binomial result is a very special…

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Clevenson–Zidek 型估计量的稳健性AI 解读

For estimating the means of several independent Poisson distributions, Clevenson and Zidek (1975) were the first to propose a class of estimators that are better than the usual one under the normalized squared error loss (1.1). This class of estimators was subsequently enlarged by others. This article examines the sensitivity of the superiority of the Clevenson-Zidek (CZ)-type means estimators over the usual one with respect to the exactness of the Poisson distribution…

Clevenson–Zidek 型估计量的稳健性AI 解读

For estimating the means of several independent Poisson distributions, Clevenson and Zidek (1975) were the first to propose a class of estimators that are better than the usual one under the normalized squared error loss (1.1). This class of estimators was subsequently enlarged by others. This article examines the sensitivity of the superiority of the Clevenson-Zidek (CZ)-type means estimators over the usual one with respect to the exactness of the Poisson distribution…

离散指数族多参数估计中改进估计量的构造AI 解读

This paper extends and unifies the theory of simultaneous estimation for the discrete exponential family. We discuss construction of estimators which theoretically dominate the uniformly minimum variance unbiased estimator (UMVUE) under a weighted squared error loss function, and show by means of computer simulation results that new simultaneous Poisson means estimators perform more favorably than those previously proposed. Our improved estimators shift the UMVUE towards a…

K 归一化平方误差损失下多个泊松参数的同时估计AI 解读

In this study, we consider the simultaneous estimation of the parameters of the distributions of $p$ independent Poisson random variables using the loss function $L_k(\lambda, \hat{\lambda}) = \sum (\lambda_i - \hat{\lambda}_i)^2/\lambda^k_i$ for a given positive integer $k$. New estimators are derived, which include the minimax estimators proposed by Clevenson and Zidek (1975), as special cases. The case when more than one observation is taken from some of the variables is…

利用均值先验假说的泊松均值联合估计AI 解读

Estimators are presented for the simultaneous estimation of p means of Poisson variables. These have significantly smaller mean square errors of estimation in the region of a pre-specified set of values, and are conservative, in the sense that their mean errors are never worse than that of the minimum variance unbiased estimator, when p > 3.

广义残差方差的最优完全等变估计量的不可容许性AI 解读

The estimation of the generalized residual variance is considered when an observable Wishart random matrix is available. It is shown that when the loss function is normalized squared error, the natural fully equivariant estimator is dominated by an alternative. The latter uses either one of two estimators depending on the result of a preliminary test of significance. This alternate estimator has an everywhere smaller mean normalized squared error than the natural estimator.