Empirical bayes approach to parameter identification in linear stochastic difference equations

Empirical Bayesian parameter estimators and predictors for linear stochastic difference equations are constructed and discussed. Some properties as consistency and asymptotic optimality are investigated. The given methods are illustrated by the example of a univariate first order autoregressive process.     

Some adjusted orthogonal,variance balanced,multidimensional block designs

A multidimensional block design (MBD) is an experimental design with d > 1 blocking criteria geometrically represented as a d-dimensional lattice with treatment varieties assigned to some or all nodes of the lattice. Intrablock analysis of variance tables for some special classes of two- and three-dimensional block designs with some empty nodes are given. Design plans and efficiencies for 31 two-dimensional designs, each universally optimal in defined classes of designs, and 7 three-dimensional designs, each nearly optimal in defined classes of designs, are listed in the appendices. A need for such designs is apparent when the blocking criteria are implemented successively and empty nodes do not represent wasted experimental units.     

Crossover designs based on type I orthogonal arrays for a self and simple mixed carryover effects model with correlated errors

We investigate the performance of crossover designs based on type I orthogonal arrays for a self and simple mixed carryover effects model in the presence of correlated errors. Assuming that between-subject errors are independent while within-subject errors behave according to the stationary first-order autoregressive and moving average processes, analytical optimality results for 3-period designs are established and, as an illustration, numerical details for a number of 4-period cases are tabulated.     

标记性制约条件及其设立的理据

标记性制约条件设立的理据是什么,历来是优选论无法明确回答的难题之一。本文对以往有关设立标记性制约条件的基础提出的各种理论观点进行评析,并以此说明优选论在发现和认识标记性制约条件方面所取得的进展。     

On optimality of a two-stage sawpling method for binomial populations

We consider a family of two-stage sampling methods for a binomial parameter that guarantee a certain precision. It is shown that, among all such methods, one due to Birnbaum and Healy minimizes the average expected second stage sample size with respect to a certain density on the parameter space. It does not, however, minimize the average expected second stage sample size with respect to the uniform density.     

On asymptotic optimality of bayes empirical bayes estimators

In an empirical Bayes decision problem, a prior distribution ? is placed on a one-dimensfonal family G of priors G_w, wεΩ, to produce a Bayes empirical Bayes estimator, The asymptotic optimaiity of the Bayes estimator is established when the support of ? is Ω and the marginal distributions H_w have monotone likelihood ratio and continuous Kullback-Leibler information number.     

ON AN APPROXIMATE OPTIMALITY CRITERION FOR THE DESIGN OF FIELD EXPERIMENTS UNDER SPATIAL DEPENDENCE

The design of large‐scale field trials where the residuals are correlated has been of recent interest, in large part because of advances in statistical and computational methods of analysis. The construction of designs for correlated data has typically used A‐optimality and is computationally intensive. This involves calculating the inverse of the information matrix for treatments under the supervision of an optimization strategy that explores the design space. We propose an approximation to A‐optimality, using nearest‐neighbour balance, that is less computationally demanding and can achieve at least 95% efficiency relative to A‐optimality in many practical situations.     

General scores statistics on ranks in the analysis of unbalanced designs

The authors consider the situation of incomplete rankings in which n judges independently rank k_i ∈ {2, …, t} objects. They wish to test the null hypothesis that each judge picks the ranking at random from the space of k_i! permutations of the integers 1, …, k_i. The statistic considered is a generalization of the Friedman test in which the ranks assigned by each judge are replaced by real‐valued functions a(j, k_i), 1 ≤ j ≤ k_i ≤ t of the ranks. The authors define a measure of pairwise similarity between complete rankings based on such functions, and use averages of such similarities to construct measures of the level of concordance of the judges' rankings. In the complete ranking case, the resulting statistics coincide with those defined by Hájek & ?idák (1967, p. 118), and Sen (1968). These measures of similarity are extended to the situation of incomplete rankings. A statistic is derived in this more general situation and its properties are investigated.     

Asymptotics of cross-validated risk estimation in estimator selection and performance assessment

Risk estimation is an important statistical question for the purposes of selecting a good estimator (i.e., model selection) and assessing its performance (i.e., estimating generalization error). This article introduces a general framework for cross-validation and derives distributional properties of cross-validated risk estimators in the context of estimator selection and performance assessment. Arbitrary classes of estimators are considered, including density estimators and predictors for both continuous and polychotomous outcomes. Results are provided for general full data loss functions (e.g., absolute and squared error, indicator, negative log density). A broad definition of cross-validation is used in order to cover leave-one-out cross-validation, V-fold cross-validation, Monte Carlo cross-validation, and bootstrap procedures. For estimator selection, finite sample risk bounds are derived and applied to establish the asymptotic optimality of cross-validation, in the sense that a selector based on a cross-validated risk estimator performs asymptotically as well as an optimal oracle selector based on the risk under the true, unknown data generating distribution. The asymptotic results are derived under the assumption that the size of the validation sets converges to infinity and hence do not cover leave-one-out cross-validation. For performance assessment, cross-validated risk estimators are shown to be consistent and asymptotically linear for the risk under the true data generating distribution and confidence intervals are derived for this unknown risk. Unlike previously published results, the theorems derived in this and our related articles apply to general data generating distributions, loss functions (i.e., parameters), estimators, and cross-validation procedures.     

基于产品卖方市场的劳工标准移植研究

市场竞争促使越来越多发展中国家企业成为劳工认证供应链的一部分。劳工标准借助于贸易平台移植到中国,对中国劳工条件甚至劳工法律制度都产生一定影响,但对现实情况的分析发现其影响还处于初级阶段。基于产品卖方主导型市场结构,采用信号模型研究中国劳工标准移植的微观机理时发现,供应商的劳工标准趋于最低要求水平是供应商借助卖方市场势力帕累托改进的结果;当公司类型的概率分布函数为凹函数时,劳工标准会收敛到最低点均衡,而非高于最低点。发展中国家处于卖方主导型市场的企业要利用劳工标准移植契机,内在提高劳工条件,让劳工信号带动产品质量提高,为更多采购商和消费者接受,以获得更大的市场势力。