Green, PJ; Thomas, A(Oxford University Press (OUP), 2013-01-01)
Full Bayesian computational inference for model determination in undirected graphical models is currently restricted to decomposable graphs or other special cases, except for small-scale problems, say up to 15 variables. ...
This paper considers the problems of estimating the stability region (domain of attraction) and controller design for uncertain linear continuous-time systems with input saturation when linear quadratic (LQ) optimal ...
In studies that involve multivariate outcomes it is often of interest to test for a common exposure effect. For example, our research is motivated by a study of neurocognitive performance in a cohort of HIV-infected women. ...
This paper presents two types of symmetric scale mixture probability distributions which include the normal, Student t, Pearson Type VII, variance gamma, exponential power, uniform power and generalised t (GT) distributions. ...
Di Guilmi, C; Gallegati, M; Ormerod, P(Elsevier Science BV, 2004-01)
Self-similar models are largely used to describe the extinction rate of biological species. In this paper we analyse the extinction rate of firms in eight OECD countries. Firms are classified by industrial sectors and ...
Delli Gatti, D; Di Guilmi, C; Gallegati, M; Gaffeo, E; Giulioni, G; Palestrini, A(World Scientific, 2008-01)
The practice of detecting power laws and scaling behaviors in economics and finance has gained momentum in the last few years, due to the increased use of concepts and methods first developed in statistical physics. Some ...
Motivation: The coiled coil is a ubiquitous a-helical protein structure domain that directs and facilitates protein¿protein interactions in a wide variety of biological processes. At the protein-sequence level, coiled coils ...
In this presentation, we developed an intuitive algorithm based on some simple concepts that were found in this study. It is more e2cient than the best-known existing algorithm. The computational complexity of the proposed ...
In this paper, "rst we develop an intuitive algorithm using the shortest path based upon the reformation of all MCs in the original network. Next, the computational complexity of the proposed algorithm is analyzed and ...
The concerns of teachers and students in integrating computer technology in the classroom may influence how computer technology is ultimately implemented. There has been substantial research into reasons for teacher ...
The seismic random vibration responses of shear beam structures with uncertainty are investigated. The structural mass and stiffness are considered as random variables. The excitations adopted are stationary or non-stationary ...
We propose a semiparametric approach to the proportional hazards regression analysis of interval-censored data. An EM algorithm based on an approximate likelihood leads to an M-step that involves maximizing a standard Cox ...
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology - thus allowing more streamlined ...
Many forensic genetics problems can be handled using structured systems of discrete variables, for which Bayesian networks offer an appealing practical modeling framework, and allow inferences to be computed by probability ...
In this paper, we propose a general optimization-based model for classification. Then we show that some well-known optimization-based methods for classification, which were developed by Shi et al. [Data mining in credit ...
Many business situations such as events, products and services, are often described in a hierarchical structure. When we use case-based reasoning (CBR) techniques to support business decision-making, we require a ...