My Master's thesis on Bayesian Classification with Regularized Gaussian Models

Covariance and correlation matrix via Rhadoop (rmr2 and HDFS)

Covariance Estimation and Denoising for Cryo-EM Images (Covariance Wiener Filtering)

An R package for testing high-dimensional covariance matrices

Algorithms for feature selection based on covariance matrix.

A Python front-end for the large-scale graphical LASSO optimizer BigQUIC (written in R).

SCFGP: Sparsely Correlated Fourier Features Based Gaussian Process

Performing the Financial Analysis on Historic Stock Market Data such as calculating various risks, returns,etc.

JED is a program for performing Essential Dynamics of protein trajectories written in Java. JED is a powerful tool for examining the dynamics of proteins from trajectories derived from MD or Geometric simulations. Currently, there are two types of PCA: distance-pair and Cartesian, and three models: COV, CORR, and PCORR.

Covariance/Correlation for big data in base R

Penalized precision matrix estimation

This R package is a wrapper around the popular "glasso" package with built-in cross validation and visualizations

Penalized precision matrix estimation via block-wise coordinate descent (graphical lasso)

Penalized precision matrix estimation via ADMM

Shrinking characteristics of precision matrix estimators

This repository contains iPython notebooks that run on the octave kernel to accompany tutorial and slides presented at PRNI

Construct portfolios along mean-variance efficient frontier

Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance