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.
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