Record ID | marc_columbia/Columbia-extract-20221130-014.mrc:98372939:3041 |
Source | marc_columbia |
Download Link | /show-records/marc_columbia/Columbia-extract-20221130-014.mrc:98372939:3041?format=raw |
LEADER: 03041pam a22003854a 4500
001 6880874
005 20221122055301.0
007 co |g|||||||||
008 080321t20092009flua b 001 0 eng
010 $a 2008013345
020 $a9781420060270 (alk. paper)
020 $a1420060279 (alk. paper)
035 $a(OCoLC)ocn214066871
035 $a(OCoLC)214066871
035 $a(NNC)6880874
035 $a6880874
040 $aDLC$cDLC$dYDX$dBTCTA$dBAKER$dYDXCP$dCDX$dOrLoB-B
050 00 $aQA278.2$b.U97 2009
082 00 $a519.5/36$222
100 1 $aUusipaikka, Esa.$0http://id.loc.gov/authorities/names/n2008020660
245 10 $aConfidence intervals in generalized regression models /$cEsa Uusipaikka.
260 $aBoca Raton, FL :$bCRC Press,$c[2009], ©2009.
300 $axxvii, 294 pages :$billustrations ;$c25 cm +$e1 CD-ROM (4 3/4 in.).
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
490 1 $aStatistics, textbooks and monographs ;$vv. 194
504 $aIncludes bibliographical references (p. 277-281) and indexes.
505 00 $g1.$tLikelihood-Based Statistical Inference -- $g2.$tGeneralized Regression Model -- $g3.$tGeneral Linear Model -- $g4.$tNonlinear Regression Model -- $g5.$tGeneralized Linear Model -- $g6.$tBinomial and Logistic Regression Model -- $g7.$tPoisson Regression Model -- $g8.$tMultinomial Regression Model -- $g9.$tOther Generalized Linear Regressions Models -- $g10.$tOther Generalized Regression Models -- $gA.$tDatasets -- $gB.$tNotation Used for Statistical Models.
520 1 $a"Confidence Intervals in Generalized Regression Models introduces a unified representation - the generalized regression model (GRM) - of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical model." "The book encompasses a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox regression model. The author also explains methods of constructing confidence regions, profile likelihood-based confidence intervals, and likelihood ratio tests." "Offering software that helps with statistical analyses, this book focuses on producing statistical inferences for data modeled by GRMs. It contains numerical and graphical results while providing the code online."--BOOK JACKET.
650 0 $aRegression analysis.$0http://id.loc.gov/authorities/subjects/sh85112392
650 0 $aConfidence intervals.$0http://id.loc.gov/authorities/subjects/sh85030927
650 0 $aLinear models (Statistics)$0http://id.loc.gov/authorities/subjects/sh85077177
650 0 $aStatistics.$0http://id.loc.gov/authorities/subjects/sh85127580
830 0 $aStatistics, textbooks and monographs ;$vv. 194.
852 00 $bmat$hQA278.2$i.U97 2009$zAccompanied by 1 CD-ROM.