JSTOR Daily

Bayesian Inference for a Normal Dispersion Matrix and Its Application to Stochastic Multiple Regression Analysis

This is a preview. Log in through your library . Abstract This paper discusses Bayesian inference procedures for a normal dispersion matrix. Structural information for the prior mean of the dispersion ...
JSTOR Daily

Evaluating Quadratic Forms of the Matrix (X'X)-1 in a Regression Analysis, with Applications

Several areas of regression analysis involve the evaluation of quadratic forms of the matrix (X'X)-1. This article draws these areas together and shows how a technique due to Salkever (1976) can be ...
GitHub

A Python project demonstrating basic linear regression with gradient descent and matrix operations, alongside scikit-learn comparison.

There was an error while loading. Please reload this page. This project implements basic linear regression from scratch using Python, providing a clear explanation of ...
IEEE

Low-Rank Matrix Regression via Least-Angle Regression

Abstract: Low-rank matrix regression is a fundamental problem in data science with various applications in systems and control. Nuclear norm regularization has been widely applied to solve this ...
IEEE

Locality-Constrained Discriminative Matrix Regression for Robust Face Identification

Abstract: Regression-based methods have been widely applied in face identification, which attempts to approximately represent a query sample as a linear combination of all training samples. Recently, ...