CSDA
2007
13 years 4 months ago
2007
We describe AMCMC, a software package for running adaptive MCMC algorithms on user-supplied density functions. AMCMC provides the user with an R interface, which in turn calls C pr...
CSDA
2007
13 years 4 months ago
2007
Partial F tests play a central role in model selections in multiple linear regression models. This paper studies the partial F tests from the view point of simultaneous confidence...
CSDA
2007
13 years 4 months ago
2007
Finite mixtures of parametric distributions are often used to model data of which it is known or suspected that there are subpopulations. Instead of a parametric model, a penalize...
CSDA
2007
13 years 4 months ago
2007
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
CSDA
2007
13 years 4 months ago
2007
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
CSDA
2007
13 years 4 months ago
2007
A fast algorithm for calculating the simplicial depth of a single parameter vector of a polynomial regression model is derived. Additionally, an algorithm for calculating the para...
CSDA
2007
13 years 4 months ago
2007
Random k-nearest-neighbour (RKNN) imputation is an established algorithm for filling in missing values in data sets. Assume that data are missing in a random way, so that missing...
CSDA
2007
13 years 4 months ago
2007
CSDA
2007
13 years 4 months ago
2007
Vector autoregressive (VAR) modelling is one of the most popular approaches in multivariate time series analysis. The parameters interpretation is simple, and provide an intuitive...