Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.

Coursework from Introduction to Machine Learning and Pattern Classification at Washington University in St. Louis. This course taught a broad introduction to machine learning and statistical pattern ...

Computer tools (R). Applications: Linear models in Regression and Classification (Bayesian Linear Regression, Generalized Linear Models, Logistic Regression), Hierarchical/ Multilevel Models, Cluster ...

That is, an LMM using a given set of SNPs for genetic similarity is equivalent to (Bayesian) linear regression using those SNPs as covariates to correct for confounding.

To this end, a quantile-regression-type structural model named as the quantile MLIRT (Q-MLIRT) model is introduced under the MLIRT framework. The parameters of the proposed model are estimated using ...

Applications: Linear models in Regression and Classification (Bayesian Linear Regression, Generalized Linear Models, Logistic Regression), Hierarchical/ Multilevel Models, Cluster Analysis and Mixture ...