Does social dominance generate prejudice? Integrating individual and contextual determinants of intergroup cognitions.

Social dominance orientation (SDO) has been proposed as an important variable in the explanation of prejudice. We distinguish between three conceptualizations of SDO: SDO as a personality trait (personality model), SDO as a moderator of the effects of situational variables (Person X Situation model), and SDO as a mediator of the effect of social position on prejudice (group socialization model [GSM]). Four studies (N = 1,657) looking at the relations between social positions, SDO, and prejudice in a natural setting and in a laboratory setting provide strong support for the GSM. In contrast to previous correlational findings, there is evidence of a cause (dominant social position), an effect (prejudice increases), and a mediator (SDO). These results suggest new perspectives on the integration of individual and contextual determinants of prejudice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A complete VARMA modelling methodology based on scalar components

Abstract. This article proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.     

Green Tax Reforms and Computational Economics A Do-it-yourself Approach

The double or even triple dividend hypothesis of green tax reforms has beena major issue of dispute in both the scientific community and the politicalarena during the last decade. Theoretical analysis has provided a number ofimportant qualitative insights to the debate but lacks of actual policyrelevance due to very restrictive assumptions. Applied research that takes thestep from stylized analytical to complex numerical models usually comes as ablackbox to non-expert modelers. This paper aims at bridging the gap betweenstylized theoretical work and numerical analysis. We develop a flexible,interactive simulation model which is accessible underhttp://brw.zew.de. Users can specify their own green tax reforms andevaluate the induced economic and environmental effects. Based on illustrativesimulations, we demonstrate the usefulness of our do-it-yourself approach fora better understanding of the double (triple) dividend hypothesis.     

Ergodicity of filtering process by vanishing discount approach

A new approach to study ergodicity of filtering processes is presented. It is based on the vanishing discount approach to discounted functional of filtering process. We show that limit superior of the Cesaro averages of the functionals is the same for all initial conditions from which the uniqueness of invariant measures of filtering processes follows. The approach is based on certain assumption for which we provide a sufficient condition using concavity arguments. In addition we show the existence of solutions to the Poisson equation corresponding to filtering process with concave functional. The assumptions are then extended to the controlled case and using similar concave arguments we obtain the existence of solutions to the Bellman equation corresponding to partially observed average cost per unit time problem.     

Parametric and nonparametric Bayesian model specification: A case study involving models for count data

In this paper we present the results of a simulation study to explore the ability of Bayesian parametric and nonparametric models to provide an adequate fit to count data of the type that would routinely be analyzed parametrically either through fixed-effects or random-effects Poisson models. The context of the study is a randomized controlled trial with two groups (treatment and control). Our nonparametric approach uses several modeling formulations based on Dirichlet process priors. We find that the nonparametric models are able to flexibly adapt to the data, to offer rich posterior inference, and to provide, in a variety of settings, more accurate predictive inference than parametric models.     

Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences.

Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate causes co-occurred with an effect. Evidence was presented in the form: AB→E; CA→E; AD→E; and so forth. In 1 story, all variables came from the same domain; in the other, the recurring candidate cause, A, came from a different domain (A was a psychological cause of a biological effect). After receiving this statistical evidence, children were asked to identify the cause of the effect on a new trial. Consistent with the predictions of a Bayesian model, all children were more likely to identify A as the cause within domains than across domains. Whereas 3.5-year-olds learned only from the within-domain evidence, 4- and 5-year-olds learned from the cross-domain evidence and were able to transfer their new expectations about psychosomatic causality to a novel task. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于Legendre多项式的随机连续系统的Markov参数估计

本文在讨论连续Ｗｉｓｅｎｒ过程的Ｌｅｇｅｎｄｒｅ多项式逼近值的相关性和Ｗｉｅｎｅｒ过程扰动下连续线性系统基于该正交多项的最小二乘估计有偏性后，提出了无偏一致的且数估计误差方差最小的Ｍａｒｋｏｖ估计（最小方差估计）算法，并给出本文方法的仿真结果。     

An object-oriented product database using ROSE

A product database for a design and manufacturing enterprise serves as a repository for the data needed to manufacture a product. This paper discusses how an object-oriented persistent object manager named ROSE, under development at Rensselaer, has been used in the Rensselaer CIM program to develop a STEP/PDES-compliant product database for its research test bed. In so doing, it provides an overview of the requirements for a product database system in an integrated design and manufacturing facility, and it discusses how the chosen system meets these requirements.