02906cam a2200361 i 4500003000800000005001700008007000300025008004100028020001500069020001800084035002300102035001900125040001800144041000800162050002500170082001200195084001500207100005500222245005000277260003100327300003500358490006000393500002000453504003000473505050900503520117501012650002502187650003002212650003002242856007902272856010402351856008902455BJBSDDR20230410132746.0ta760807s1977    nyua     b    001 0 eng    a0471019674  a9780471019671  a(OCoLC)ocm02401871  a(OCoLC)2401871  aDLCcDLCbspa  aspa00aQA 278.2bS443l 197700a519.536  a31.732bcl1 aSeber, G. A. F.q(George Arthur Frederick),d1938-10aLinear regression analysis /cG. A. F. Seber.  aNew York :bWiley,cc1977.  axvii, 465 p. :bill. ;c24 cm.0 aWiley series in probability and mathematical statistics  aIncludes index.  aBibliography: p. 433-457.0 a1. Vectors of random variables -- 2. Multivariate normal distribution -- 3. Linear regression: estimation and distribution theory -- 4. Linear regression: hypothesis testing -- 5. Confidence intervals and regions -- 6. Departures from underlying assumptions -- 7. Straight-line regression -- 8. Polynomial regression -- 9. Analysis of variance -- 10. Analysis of covariance and missing observations -- 11. Computational techniques for fitting a specified regression -- 12. Choosing the "best" regression.  aThis book explains the theory and application of research techniques used in linar regression analysis. Dr. Seber gives a full discussion on the assumptions underlying regression models, and presents a variety of graphic and computational techniques for investigating these assumptions. His geometric approach enables the reader to deal with full rank and less than full rank models at the same time, and he varies the material by using the theory of generalized inverses to explain other approaches. Seber gives special attention to cases in straight-line and polynomial regression, analysis of variance and co-variance models associated with experimental designs in a theoretical framework. He also includes a number of topics which are usually omitted from most books, but are important in this area: optimal design, ridge estimators, two-phase regression, spline functions, and missing observations-with up-to-date sources of the literature available in these areas. Over 200 carefully selected problems, outline solutions, a reference bibliography, and appendices make this one of the most useful and informative books available on the subject of linear regression. 0aRegression analysis. 6aAnalyse de râegression. 4aAnálisis de regresión4 3Table of Contents onlyuhttp://www.loc.gov/catdir/toc/onix01/76040117.html423Contributor biographical informationuhttp://www.loc.gov/catdir/enhancements/fy0607/76040117-b.html423Publisher descriptionuhttp://www.loc.gov/catdir/enhancements/fy0607/76040117-d.html