LEADER 00907nam0-22003371i-450- 001 990002007390403321 005 20110705111604.0 035 $a000200739 035 $aFED01000200739 035 $a(Aleph)000200739FED01 035 $a000200739 100 $a20030910d1965----km-y0itay50------ba 101 0 $aeng 102 $aUS 105 $ay---a---001yy 200 1 $aMolecular and cellular aspects of development$f[edited by] Eugene Bell 210 $aNew York$cHarper & Row$d1965 215 $a525 p.$d26 cm 610 0 $aCellule 610 0 $aCitologia 676 $a574.87 702 1$aBell,$bEugene 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002007390403321 952 $a61 III B.8/35$b2326$fDAGEN 952 $aIIIe C 38$bInv.$fDMVSF 959 $aDAGEN 959 $aDMVSF 996 $aMolecular and cellular aspects of development$9402726 997 $aUNINA LEADER 04081nam 22008535 450 001 9910438158603321 005 20251116201957.0 010 $a9783642343339 010 $a3642343333 024 7 $a10.1007/978-3-642-34333-9 035 $a(CKB)2670000000360433 035 $a(EBL)1082796 035 $a(SSID)ssj0000904267 035 $a(PQKBManifestationID)11447719 035 $a(PQKBTitleCode)TC0000904267 035 $a(PQKBWorkID)10920642 035 $a(PQKB)10561196 035 $a(DE-He213)978-3-642-34333-9 035 $a(MiAaPQ)EBC6314567 035 $a(MiAaPQ)EBC1082796 035 $a(Au-PeEL)EBL1082796 035 $a(CaPaEBR)ebr10969161 035 $a(OCoLC)845247477 035 $a(PPN)170490467 035 $a(EXLCZ)992670000000360433 100 $a20130509d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRegression $eModels, Methods and Applications /$fby Ludwig Fahrmeir, Thomas Kneib, Stefan Lang, Brian Marx 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (828 p.) 300 $aDescription based upon print version of record. 311 08$a9783642343322 311 08$a3642343325 327 $aIntroduction -- Regression Models -- The Classical Linear Model -- Extensions of the Classical Linear Model -- Generalized Linear Models -- Categorical Regression Models -- Mixed Models -- Nonparametric Regression -- Structured Additive Regression -- Quantile Regression -- A Matrix Algebra -- B Probability Calculus and Statistical Inference -- Bibliography -- Index. 330 $aThe aim of this book is an applied and unified introduction into parametric, non- and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through many real data examples and case studies. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written on an intermediate mathematical level and assumes only knowledge of basic probability, calculus, and statistics. The most important definitions and statements are concisely summarized in boxes. Two appendices describe required matrix algebra, as well as elements of probability calculus and statistical inference. 606 $aStatistics 606 $aStatistics 606 $aEconometrics 606 $aBiometry 606 $aEpidemiology 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aStatistical Theory and Methods 606 $aEconometrics 606 $aBiostatistics 606 $aStatistics 606 $aEpidemiology 615 0$aStatistics. 615 0$aStatistics. 615 0$aEconometrics. 615 0$aBiometry. 615 0$aEpidemiology. 615 14$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aStatistical Theory and Methods. 615 24$aEconometrics. 615 24$aBiostatistics. 615 24$aStatistics. 615 24$aEpidemiology. 676 $a519.536 700 $aFahrmeir$b L.$4aut$4http://id.loc.gov/vocabulary/relators/aut$089111 702 $aKneib$b Thomas$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aLang$b Stefan$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMarx$b Brian$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910438158603321 996 $aRegression$91443768 997 $aUNINA