20 search results - page 3 / 4 » Parametric Sensitivity Analysis Using Large-Sample Approxima... |
IDA
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. We present a probabilistic model for robust principal component analysis (PCA) in which the observation noise is modelled by Student-t distributions that are independent ...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
SADM
2010
13 years 2 months ago
2010
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
CSDA
2008
13 years 7 months ago
2008
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
This paper investigates a Bayesian model and a Markov chain Monte Carlo (MCMC) algorithm for gene factor analysis. Each sample in the dataset is decomposed as a linear combination...