This book describes the development of what we would now regard as a class of statistical fitting procedures between 1750 and 1900. The book contains detailed algebraic descriptions of the fitting of linear relationships by the method of least squares and the closely related least absolute deviations and minimax absolute deviations procedures. The prerequisite is a basic course in mathematical statistics. The primary audience for this book will be statisticians concerned with the fitting of linear models. However, it will also be of interest to engineers and scientists concerned with the empirical determination of linear relationships.

"Examines classic algorithms, geometric diagrams, and mechanical principles for enhances visualization of statistical estimation procedures and mathematical concepts in physics, engineering, and computer programming."

Examines classic algorithms, geometric diagrams, and mechanical principles for enhancing visualization of statistical estimation procedures and mathematical concepts in physics, engineering, and computer programming.

Presenting numerous algorithms in a simple algebraic form so that the reader can easilytranslate them into any computer language, this volume gives details of several methodsfor obtaining accurate least squares estimates. It explains how these estimates may beupdated as new information becomes available and how to test linear hypotheses.Linear Least Squares Computations features many structured exercises that guidethe reader through the available algorithms, plus a glossary of commonly used terms anda bibliography of supplementary reading ... collects "ancient" and modem results onlinear least squares computations in a convenient single source . . . develops the necessarymatrix algebra in the context of multivariate statistics . .. only makes peripheral use ofconcepts such as eigenvalues and partial differentiation .. . interprets canonical formsemployed in computation ... discusses many variants of the Gauss, Laplace-Schmidt,Givens, and Householder algorithms ... and uses an empirical approach for the appraisalof algorithms.Linear Least Squares Computations serves as an outstanding reference forindustrial and applied mathematicians, statisticians, and econometricians, as well as atext for advanced undergraduate and graduate statistics, mathematics, and econometricscourses in computer programming, linear regression analysis, and applied statistics.

This book describes the development of statistics, which for more than a century was called "the calculus of observations." The approach will help readers gain a clearer understanding of the historical development as well as the essential nature of some of the commonly used statistical estimation procedures. Detailed descriptions of the fitting of linear relationships by the method of least squares and the closely related least absolute deviations and minimax absolute deviations procedures are presented, along with some of the important work by Laplace, Gauss, and Adrain.