Distributions with Generalized Skewed Conditionals and Mixtures of Such Distributions

Mixtures of skewed distributions (univariate and bivariate) provide flexible models. An alternative modeling approach involves distributions with skewed conditional distributions and mixtures of such distributions. We consider the interrelationships between such models. Examples are provided to show that several skewed distributions already considered in the literature can be viewed as having been constructed via a combination of mixing and skewing.     

Two Conditionally Specified Mixed Binomial Distributions

Two generalized hypergeometric distributions are identified as mixed binomial distributions by conditional specification. Both distributions show profiles that are not possible in other mixed binomial distributions such as the beta-binomial distribution. A simulation study illustrates that beta-binomial distribution is more precise to fit data with usual profiles but the two distributions presented can improve the capability of fitting data in other less common scenes.     

An observation on regression-based specification tests

The use of regression-based specification tests, such as the nR² form of the Lagrange Multiplier test, has become quite widespread over the last 20 years. The popularization of the nR² form of the Lagrange Multiplier (LM) test, perhaps the most widely used class of regression-based tests, has come about in large part from the ease of its application to many tests of nonlinear restrictions and its asymptotic equivalence to Likelihood Ratio and Wald tests. Properly performed, these regression-based tests invariably include regressors which are orthogonal by construction to the dependent variable of the regression. The purpose of this paper is to motivate the inclusion of such variables by investigating implications for the test size and power if these regressors are erroneously omitted. It is straightforward to show that both the size and power of the test are adversely affected by omitting these regressors.     

The relation between unemployment and interest rate:

In bierens (1987) a granger casual relation was found between unemployment and the interest rate for the netherlands. In the present paper we will investigate whether there exists a similar granger casual relation between unemployment and interest rate for a number of other countries. It appears that, with our ARMAX modeling approach, this relationship is not confined to the netherlands, but also holds for the USA, Canada, Japan, Germany, the UK and France. For these countries the interest rate is the main explanatory variable, together with industrial production (the latter with one exception), whereas for most countries the wage rate is of minor or no importance as a determinant of unemployment. A number of economic theories can explain these phenomena of which the revenue maximization theory of baumol (1959) augmented with a flexible labor effort rate seems quite realistic     

Residual-based specification of the random-effects distribution for cluster data

We propose a method for specifying the distribution of random effects included in a model for cluster data. The class of models we consider includes mixed models and frailty models whose random effects and explanatory variables are constant within clusters. The method is based on cluster residuals obtained by assuming that the random effects are equal between clusters. We exhibit an asymptotic relationship between the cluster residuals and variations of the random effects as the number of observations increases and the variance of the random effects decreases. The asymptotic relationship is used to specify the random-effects distribution. The method is applied to a frailty model and a model used to describe the spread of plant diseases.     

Impact study of volatility modelling of Bangladesh stock index using non-normal density

This article examines a wide variety of popular volatility models for stock index return, including the random walk (RW), autoregressive, generalized autoregressive conditional heteroscedasticity (GARCH), and asymmetric GARCH models with normal and non-normal (Student's t and generalized error) distributional assumption. Fitting these models to the Chittagong stock index return data from the period 2 January 1999 to 29 December 2005, we found that the asymmetric GARCH/GARCH model fits better under the assumption of non-normal distribution than under normal distribution. Non-parametric specification tests show that the RW-GARCH, RW-TGARCH, RW-EGARCH, and RW-APARCH models under the Student's t-distributional assumption are significant at the 5% level. Finally, the study suggests that these four models are suitable for the Chittagong Stock Exchange of Bangladesh. We believe that this study would be of great benefit to investors and policy makers at home and abroad.     

“意象思维”与三星堆文化造型艺术

从考古学的角度看，三星堆出土的主要器物显示出古蜀人已迈入了文明的门槛。从文化人类学的角度看，古蜀人的思雏以原始“意象思维”为主，这决定了三星堆文化造型艺术的模仿性、具体性、象征性。     

Specification Tests for Random-effects Transition Models: An Application to a Model of the British Youth Training Scheme

We develop diagnostic tests for random-effects multi-spell multi-state models focusing on: independence between the unobserved heterogeneity and observed covariates; mutual independence of heterogeneity terms; and distributional form. They are applied to a transition model of the British youth labor market, revealing significant misspecifications in our initial model, and allowing us to develop a considerably better-fitting specification that would have been difficult to reach by other means. The improved specification implies reduced estimates of the effectiveness of the youth training scheme (YTS), but we nevertheless retain the conclusion of significant positive effects of YTS on employment prospects.     

A statistical framework for ecological and aggregate studies

Inference from studies that make use of data at the level of the area, rather than at the level of the individual, is more difficult for a variety of reasons. Some of these difficulties arise because frequently exposures (including confounders) vary within areas. In the most basic form of ecological study the outcome measure is regressed against a simple area level summary of exposure. In the aggregate data approach a survey of exposures and confounders is taken within each area. An alternative approach is to assume a parametric form for the within-area exposure distribution. We provide a framework within which ecological and aggregate data studies may be viewed, and we review some approaches to inference in such studies, clarifying the assumptions on which they are based. General strategies for analysis are provided including an estimator based on Monte Carlo integration that allows inference in the case of a general risk–exposure model. We also consider the implications of the introduction of random effects, and the existence of confounding and errors in variables.     

关于大学教学督导工作的几点看法

本文简述了大学教学督导工作的涵义、作用、督导方式以及督与导的关系的处理问题 ,探讨了大学课堂教学督导的过程 ,并就教学中的一些常见问题进行了分析