AI Chat AI Image Generator AI Video Text to Speech

Correlation Estimation System Minimization Compared to Least Squares Minimization in Simple Linear Regression

02/07/2018

∙

by Rudy Gideon, et al.

∙

∙

A general method of minimization using correlation coefficients and order statistics is evaluated relative to least squares procedures in the estimation of parameters for normal data in simple linear regression.

page 1

page 2

page 3

page 4

research

∙ 07/07/2013

Loss minimization and parameter estimation with heavy tails

This work studies applications and generalizations of a simple estimatio...

0 Daniel Hsu, et al. ∙

research

∙ 01/17/2019

Model-Free Tests for Series Correlation in Multivariate Linear Regression

Testing for series correlation among error terms is a basic problem in l...

0 Yanqing Yin, et al. ∙

research

∙ 09/29/2021

Assessing the goodness of fit of linear regression via higher-order least squares

We introduce a simple diagnostic test for assessing the goodness of fit ...

0 Christoph Schultheiss, et al. ∙

research

∙ 10/10/2018

Using Normalized Cross Correlation in Least Squares Optimizations

Direct methods for vision have widely used photometric least squares min...

0 Oliver J. Woodford, et al. ∙

research

∙ 04/18/2021

Linear shrinkage for predicting responses in large-scale multivariate linear regression

We propose a new prediction method for multivariate linear regression pr...

0 Yihe Wang, et al. ∙

research

∙ 10/20/2022

Iteratively Reweighte Least Squares Method for Estimating Polyserial and Polychoric Correlation Coefficients

An iteratively reweighted least squares (IRLS) method is proposed for es...

0 Peng Zhang, et al. ∙

research

∙ 03/17/2020

Linear Regression without Correspondences via Concave Minimization

Linear regression without correspondences concerns the recovery of a sig...

0 Liangzu Peng, et al. ∙