Nature

Bayesian Estimation and Maximum Likelihood Methods

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
JSTOR Daily

Empirical Bayes Hierarchical Models for Regularizing Maximum Likelihood Estimation in the Matrix Gaussian Procrustes Problem

This is a preview. Log in through your library . Abstract Procrustes analysis involves finding the optimal superposition of two or more "forms" via rotations, translations, and scalings. Procrustes ...
mccormick.northwestern.edu

ELEC_ENG 433: Statistical Pattern Recognition

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...
JSTOR Daily

Approximate Likelihood-Ratio Test for Branches: A Fast, Accurate, and Powerful Alternative

We revisit statistical tests for branches of evolutionary trees reconstructed upon molecular data. A new, fast, approximate likelihood-ratio test (aLRT) for branches is presented here as a competitive ...
mccormick.northwestern.edu

ELEC_ENG 433: Statistical Pattern Recognition

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...