There have been several efforts to build life-like autonomous creatures in virtual worlds, but only few of them have focused their intentions in presenting human-like autonomous creatures. In this paper we discuss the problem of building autonomous virtual humanoids with goal directed behaviors. We present the decision-making as a process compound of: goal achievement planning, dynamic belief m...

Given a collection of single-market covariance matrix forecasts for different markets, we describe how to embed them into a global forecast of total risk. We do this by starting with any global covariance matrix forecast that contains information about cross-market correlations, and revising it to agree with the pre-specified submarket matrices, preserving the requirement that a covariance matr...

In this paper we investigate the properties of the covariance matrices associated with variational Bayesian approximations, based on data from mixture models, and compare them with the true covariance matrices, corresponding to Fisher information matrices. It is shown that the covariance matrices from the variational Bayes approximations are normally ‘too small’ compared with those for the maxi...

Previous chapters discussed the retrospective analysis of regime shifts. By retrospective, I mean the backward-looking process of examining data, fitting models, and drawing inferences about which models are appropriate descriptions of the ecosystem’s behavior. The retrospective study of regime shifts is difficult, primarily because regime shifts are relatively uncommon events. Nevertheless, re...

maternal effects on body weight at 8 weeks of age (bw8w), egg weight (ew), egg number (en) and age at sexual maturity (asm) from 13 generations of mazandaran native fowl were investigated. the data were analyzed using restricted maximum likelihood procedures and animal model with dfreml software. with or without using maternal effects, six different animal models were fitted. likelihood ratio t...

We present some methods for graphing distributions of covariance matrices and demonstrate them on several models, including the Wishart, inverse-Wishart, and scaled inverse-Wishart families in different dimensions. Our visualizations follow the principle of decomposing a covariance matrix into scale parameters and correlations, pulling out marginal summaries where possible and using two and thr...

A computationally e cient method for structured covariance matrix estimation is presented. The proposed method provides an Asymptotic (for large samples) Maximum Likelihood estimate of a structured covariance matrix and is referred to as AML. A closed-form formula for estimating Hermitian Toeplitz covariance matrices is derived which makes AML computationally much simpler than most existing Her...