A01=Farebrother
A01=R.W. Farebrother
advanced least squares algorithms
Author_Farebrother
Author_R.W. Farebrother
Category=PBW
Doolittle's Method
Doolittle’s Method
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Exact Linear Relationship
Full Column Rank
Gauss Jordan Method
Gauss's Method
Gauss's Procedure
gausss
Gauss’s Method
Gauss’s Procedure
Householder Transformation
Householder's Procedure
householders
Householder’s Procedure
hypothesis testing methods
Instrumental Variable Estimator
Longley's Data
Longley’s Data
lower
Lower Triangular Matrix
matrix
matrix decomposition
Minimum Variance Unbiased Linear Estimator
model
multivariate statistics
numerical optimization
orthonormal
Orthonormal Matrices
Orthonormal Matrix
Orthonormalization Procedure
Positive Semidefinite Matrix
procedure
R. W. Farebrother
Recursive Residuals
regression diagnostics
Row Interchanges
Small Changes
Stack
standard
Standard Linear Model
statistical computing
triangular
Triangular Matrix
Unbiased Estimator
Unbiased Linear Estimator
variance
Variance Matrix
Product details
- ISBN 9780824776619
- Weight: 544g
- Dimensions: 156 x 234mm
- Publication Date: 19 Feb 1988
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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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.
