Doing Least Squares: Perspectives from Gauss and Yule

1998/04/01 by John Aldrich · 2 citations
Mathematics · #Statistical and numerical algorithms

paper · doi:10.1111/j.1751-5823.1998.tb00406.x

openalex publication_date 1998/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23

Abstract

Summary Gauss introduced a procedure for calculating least squares estimates and their precisions. Yule introduced a new system of notation adapted to correlation analysis. This paper describes these formalisms and compares them with the matrix and vector space formalisms used in modern regression analysis.

Citations

• The distribution of quadratic forms in a normal system, with applications to the analysis of covariance

Cited by

• Fisher and Regression
• Least squares [wikipedia]