Empirical Bayes rules and Gaussian processes

In this paper we study empirical Bayes (e.B.) rules from a viewpoint which has not yet got any attention in the literature. Since an e.B. estimator can be seen as an estimate of an unknown function, namely the true Bayes estimator, it is natural to consider e.B. estimators as stochastic processes. In this paper we make a first attempt in the direction of this approach. For a certain class of e.B. estimators for the continuous one-parameter exponential family, we investigate the global behaviour on finite intervals. It is shown that the difference between the e.B. and the true Bayes estimator can be represented as a certain type of Gaussian process plus a remainder which is uniformly of smaller order. Several applications of this result are given.     

An industrial application of meta-evaluation

This article describes the efforts of an industrial training organization to increase the number and to improve the quality of “follow-up” evaluations (i.e., evaluations in terms of post-training job performance). Efforts included an analysis of the problems encountered in evaluating training, development and implementation of corrective actions, and an evaluation of the corrective actions. The project illustrates the process of “meta-evaluations.”     

Sequential procedures based on M-estimators with discontinuous score functions

Bounded-width sequential confidence intervals and sequential tests for regression parameter based on M-estimators are extended to the case where the score-functions generating the M-estimators have jump-discontinuities. In the context of the asymptotic normality of the stopping variable, for the confidence interval problem, it is observed that the jump-discontinuities induce a slower rate of convergence. The proofs of the main theorems rest on the weak convergence of some related processes and this is also studied.     

A股市场中市盈率应用的若干问题——关于市盈率问题的若干研究(下)

"A股市场中市盈率应用的若干问题"是上期论文"关于市盈率问题的若干研究"的下篇,它以本轮熊市为背景,借助于数量化方法,研究与探讨了在A股市场及其投资的几个重要方面(如价值评估、投资分析、决策及回报等)中,使用市盈率指标的一些问题。     

Can the Augmented Solow Model with Migration Explain the Italian Internal Brain Drain?

We extend the Dolado et al. (1994) model to both inflows and outflows of migrants and assume that they have a human capital endowment that contributes to increase/decrease the stock of human capital in the receiving/sending economy. We derive the conditional convergence equation in which the impact of migration flows on the growth rate is disentangled in a pure quantity effect and in a quality or composition effect of immigration and emigration rates that accounts for the relative human capital endowment of migrants with respect to resident population. Next, we test the model with Italian regional data for the 1970–2005 time period. We find that the model provides a good explanation of the Italian experience. The quantity effect is negative for the immigration rate and positive for the emigration rate, whereas the composition effect is positive for immigration and negative for emigration. Finally, we separate the centre‐north from the south and find that the composition effect of emigration is stronger for the latter. We interpret these results as a clear evidence of a brain drain from the Mezzogiorno to the centre‐northern regions.     

中国粮食价格波动特征研究——基于X-12-ARIMA模型和ARCH类模型

以小麦和大豆为例,研究2002年1月至2012年6月中国粮食价格波动特征。首先利用X-12-ARIMA模型对价格序列进行季节调整,然后运用ARCH类模型对剥离季节因素的价格序列进行波动分析。结果发现:中国粮食价格季节性波动逐年减弱;粮食价格具有明显的波动集簇性,前期价格波动和外部冲击对后期价格的影响具有持续性;粮食市场不存在"高风险、高回报"特征;小麦价格波动的非对称性不显著,而大豆价格波动则呈现明显的非对称特征,且上期价格上涨信息引发的波动要大于下跌信息。     

Robust location estimation with missing data

In a missing data setting, we have a sample in which a vector of explanatory variables ${\bf x}_i$ is observed for every subject i, while scalar responses $y_i$ are missing by happenstance on some individuals. In this work we propose robust estimators of the distribution of the responses assuming missing at random (MAR) data, under a semiparametric regression model. Our approach allows the consistent estimation of any weakly continuous functional of the response's distribution. In particular, strongly consistent estimators of any continuous location functional, such as the median, L‐functionals and M‐functionals, are proposed. A robust fit for the regression model combined with the robust properties of the location functional gives rise to a robust recipe for estimating the location parameter. Robustness is quantified through the breakdown point of the proposed procedure. The asymptotic distribution of the location estimators is also derived. The proofs of the theorems are presented in Supplementary Material available online. The Canadian Journal of Statistics 41: 111–132; 2013 © 2012 Statistical Society of Canada     

Nonlinear unbiased estimation in linear models †

In the paper the problem of nonlinear unbiased estimation of expectation in linear models is considered. The considerations are restricted to linear plus quadratic estimators with quadratic parts invariant under a group of translations. The one way classification model is considered in detail, for which an explicit formula for the locally best estimators is presented. A numerical evaluation of variances of the best estimators is given for some unbalanced one way classification models and compared with the variance of the ordinary linear estimators.