Response-Response Relationships in Organizational Behavior Management

Abstract

The issue of behavioral covariation has been a topic of interest to behavior analysts for many years. Many writers have used the term response generalization interchangeably with behavioral covariation. In this paper, we argue from the extant literature that the term “response generalization” should be used to describe only very specific occasions of behavioral covariation. In fact, we argue, response generalization is merely one of at least six types of behavioral covariation observed in organizational behavior management studies. After describing response generalization, the remaining five types of response-response relations we describe are: (1) physiological relations, (2) when target behaviors occasion related behaviors, (3) when target behaviors reinforce related behaviors, (4) when target and related behaviors are maintained by the same reinforcing stimulus, and (5) covariation through participation in verbal relations. We conclude by discussing the potential for additional research on this topic in the area of verbal relations.     

一种基于加权F-范数的半正定矩阵的逼近方法

正定性是许多金融预测模型的重要假设前提，然而从实际样本中得到的相关系数矩阵并不能保证其正定性。为此在介绍如何根据样本设定相关系数矩阵以及范数逼近原理的基础上，如何根据该原理找到与之最接近的相关系数矩阵，即最接近的单位对角半正定对称矩阵。通过实证，验证了其方法的有效性。     

Factor Multivariate Stochastic Volatility via Wishart Processes

This paper proposes a high dimensional factor multivariate stochastic volatility (MSV) model in which factor covariance matrices are driven by Wishart random processes. The framework allows for unrestricted specification of intertemporal sensitivities, which can capture the persistence in volatilities, kurtosis in returns, and correlation breakdowns and contagion effects in volatilities. The factor structure allows addressing high dimensional setups used in portfolio analysis and risk management, as well as modeling conditional means and conditional variances within the model framework. Owing to the complexity of the model, we perform inference using Markov chain Monte Carlo simulation from the posterior distribution. A simulation study is carried out to demonstrate the efficiency of the estimation algorithm. We illustrate our model on a data set that includes 88 individual equity returns and the two Fama-French size and value factors. With this application, we demonstrate the ability of the model to address high dimensional applications suitable for asset allocation, risk management, and asset pricing.     

Reduced Rank Discrimination

In this paper the problem of classifying an individual with p characteristics into one of k multivariate normal distributions with common unknown covariance matrix is considered when the matrix of ( k +1) means has a linear structural relationship, that is, it lies in an r -dimensional plane, where r 相似文献   

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ABSTRACT

We extend Chebyshev's inequality to a random vector with a singular covariance matrix. Then we consider the case of a multivariate normal distribution for this generalization.