Using simulation methods for bayesian econometric models: inference,development and communication: some comments

We extend the average derivatives estimator to the case of functionally dependent regressors. We show that the proposed estimator is consistent and has a limiting normal distribution. A consistent covariance matrix estimator for the proposed estimator is provided.     

论3G时代高校图书馆的发展

3G时代图书馆工作面临新的考验。为了应对这一革命性的冲击，高校图书馆要做好数字化的核心准备工作，逐步建立并完善例如“手机图书馆”的建设。一方面可以提高数字化图书的普及与使用率，另一方面也可以在演进的过程中确实保护高校的既得利益。     

Hugh George Brennan: Glasgow University’s First Lecturer in Russian

To date little has been known, and less written, about the life of Hugh George Brennan, Glasgow University's first lecturer in Russian. The uncovering of previously unused Russian and British sources throwing fresh light on his life, intellectual development and occupations has made possible a fuller assessment of a significant figure in Glasgow's contribution to Slavonic Studies. Brennan lived and taught in Russia for 20 years. The resulting intense and unusually intimate experience of Russian life probably explains unconventional aspects of his Glasgow appointment. Brennan was an undoubted educational and social success in Russia. Events in the shape of the February Revolution of 1917 forced him to return to Britain. Glasgow's timely offer of a new position was the start of a very different life. This aspect of Brennan's career is reviewed mainly through his commitment to extensive public activities.     

Behavior Change and the Freshman 15: Tracking Physical Activity and Dietary Patterns in 1st-Year University Women

Objective and Participants: The authors assessed the stability of diet and physical activity and their relationship to weight changes in first-year university women. Methods: They collected anthropometric and body composition data from 101 resident women at the beginning of their first year of college and again at 12 months. The authors obtained physical activity and dietary logs 4 times throughout the year. Results: Caloric intake decreased over 12 months in all participants (p = .01). There was little change in physical activity in participants who lost weight (p = .73, d = .18). Those who gained weight experienced a trend toward decreased physical activity (p = .13, d = .38). A significant Time X Group interaction on physical activity (p = .04) suggests that physical activity patterns differed substantially between individuals who gained weight and those who lost weight. Conclusions: Reduction in physical activity appears to be the defining characteristic in freshman weight gain.     

Consumer bankruptcy and default: The role of individual social capital

In this paper, we empirically assess the role of individual social capital on personal bankruptcy and default outcomes in the consumer credit market. After controlling for a borrower’s risk score, debt, income, wealth, and legal and economic environments, we find that default/bankruptcy risk rises and then falls over the lifecycle, while a borrower who owns a home or is married has a lower risk of default/bankruptcy. Moreover, a borrower who migrates 190 miles from his “state of birth” is 17% more likely to default and 15% more likely to file for bankruptcy, while a borrower who continues to live in his state of birth is 14% and 10% less likely to default and file for bankruptcy, respectively. A borrower who moves to a rural area is 9% and 7% less likely to default and declare bankruptcy, respectively. We also find that measures of social networks, norms, and cooperation and trust (i.e., aggregate social capital) are inversely related to consumer bankruptcy.     

Parameter estimation of state space models for univariate observations

This paper contributes to the problem of estimation of state space model parameters by proposing estimators for the mean, the autoregressive parameters and the noise variances which, contrarily to maximum likelihood, may be calculated without assuming any specific distribution for the errors. The estimators suggested widen the scope of the application of the generalized method of moments to some heteroscedastic models, as in the case of state-space models with varying coefficients, and give sufficient conditions for their consistency. The paper includes a simulation study comparing the proposed estimators with maximum likelihood estimators. Finally, these methods are applied to the calibration of the meteorological radar and estimation of area rainfall.     

Strong laws of large numbers for dependent heterogeneous processes: a synthesis of recent and new results

This paper surveys recent developments in the strong law of large numbers for dependent heterogeneous processes. We prove a generalised version of a recent strong law for Lz-mixingales, and also a new strong law for Lpmixingales. These results greatly relax the dependence and heterogeneity conditions relative to those currently cited, and introduce explicit trade-offs between dependence and heterogeneity. The results are applied to proving strong laws for near-epoch dependent functions of mixing processes. We contrast several methods for obtaining these results, including mapping directly to the mixingale properties, and applying a truncation argument.     

Methods for calculating stationary distribution in linear models of time series

The article deals with methods for computing the stationary marginal distribution in linear models of time series. Two approaches are described. First, an algorithm based on approximation of solution of the corresponding integral equation is briefly reviewed. Then, we study the limit behaviour of the partial sums c ₁ η₁+c ₂ η₂+···+c _n η _n where η _i are i.i.d. random variables and c _i real constants. We generalize procedure of Haiman (1998) [Haiman, G., 1998, Upper and lower bounds for the tail of the invariant distribution of some AR(1) processes. Asymptotic Methods in Probability and Statistics, 45, 723–730.] to an arbitrary causal linear process and relax the assumptions of his result significantly. This is achieved by investigating the properties of convolution of densities.     

Nonparametric regression with cross‐classified responses

In this article, we develop regression models with cross‐classified responses. Conditional independence structures can be explored/exploited through the selective inclusion/exclusion of terms in a certain functional ANOVA decomposition, and the estimation is done nonparametrically via the penalized likelihood method. A cohort of computational and data analytical tools are presented, which include cross‐validation for smoothing parameter selection, Kullback–Leibler projection for model selection, and Bayesian confidence intervals for odds ratios. Random effects are introduced to model possible correlations such as those found in longitudinal and clustered data. Empirical performances of the methods are explored in simulation studies of limited scales, and a real data example is presented using some eyetracking data from linguistic studies. The techniques are implemented in a suite of R functions, whose usage is briefly described in the appendix. The Canadian Journal of Statistics 39: 591–609; 2011. © 2011 Statistical Society of Canada