Stat-Co
Limit theorems for some adaptive MCMC algorithms with subgeometric kernels: Part II
Bayesian Core: The Complete Solution Manual
On Bayesian Curve Fitting Via Auxiliary Variables
D-optimal designs via a cocktail algorithm
Regression on a Graph
Particle filtering within adaptive Metropolis Hastings sampling
Probability matrices, non-negative rank, and parameterizations of mixture models
Using the Eigenvalue Relaxation for Binary Least-Squares Estimation Problems
A black box method for solving the complex exponentials approximation problem
ADIS - A robust pursuit algorithm for probabilistic, constrained and non-square blind source separation with application to fMRI
Maximum Likelihood Estimation for Markov Chains
Skellam shrinkage: Wavelet-based intensity estimation for inhomogeneous Poisson data
A Comparison of Analysis of Covariate-Adjusted Residuals and Analysis of Covariance
Variational inference for large-scale models of discrete choice
Gibbs Sampling for a Bayesian Hierarchical General Linear Model
Compressive Sensing Using Low Density Frames
Adjusted Viterbi training for hidden Markov models
Deconvolution by simulation
On The Density Estimation by Super-Parametric Method
Stability of the Gibbs Sampler for Bayesian Hierarchical Models
The Algebraic Complexity of Maximum Likelihood Estimation for Bivariate Missing Data
Fast stable direct fitting and smoothness selection for Generalized Additive Models
