LEADER 04174nam 22006615 450 001 9910484980203321 005 20250311210915.0 010 $a9783030637576 010 $a3030637573 024 7 $a10.1007/978-3-030-63757-6 035 $a(CKB)4100000011797533 035 $a(DE-He213)978-3-030-63757-6 035 $a(MiAaPQ)EBC6516223 035 $a(Au-PeEL)EBL6516223 035 $a(OCoLC)1242026524 035 $a(PPN)254719856 035 $a(EXLCZ)994100000011797533 100 $a20210312d2021 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Course on Small Area Estimation and Mixed Models $eMethods, Theory and Applications in R /$fby Domingo Morales, María Dolores Esteban, Agustín Pérez, Tomá? Hobza 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (XX, 599 p. 373 illus., 10 illus. in color.) 225 1 $aStatistics for Social and Behavioral Sciences,$x2199-7365 311 08$a9783030637569 311 08$a3030637565 327 $a1 Small Area Estimation -- 2 Design-based Direct Estimation -- 3 Design-based Indirect Estimation -- 4 Prediction Theory -- 5 Linear Models -- 6 Linear Mixed Models -- 7 Nested Error Regression Models -- 8 EBLUPs under Nested Error Regression Models -- 9 Mean Squared Error of EBLUPs -- 10 EBPs under Nested Error Regression Models -- 11 EBLUPs under Two-fold Nested Error Regression Models -- 12 EBPs under Two-fold Nested Error Regression Models -- 13 Random Regression Coefficient Models -- 14 EBPs under Unit-level Logit Mixed Models -- 15 EBPs under Unit-level Two-fold Logit Mixed Models -- 16 Fay-Herriot Models -- 17 Area-level Temporal Linear Mixed Models -- 18 Area-level Spatio-temporal Linear Mixed Models -- 19 Area-level Bivariate Linear Mixed Models -- 20 Area-level Poisson Mixed Models -- 21 Area-level Temporal Poisson Mixed Models -- A Some Useful Formulas -- Index. 330 $aThis advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians. . 410 0$aStatistics for Social and Behavioral Sciences,$x2199-7365 606 $aSocial sciences$xStatistical methods 606 $aStatistics 606 $aStatistics$xComputer programs 606 $aStatistics 606 $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 606 $aStatistical Theory and Methods 606 $aStatistical Software 606 $aStatistics in Business, Management, Economics, Finance, Insurance 615 0$aSocial sciences$xStatistical methods. 615 0$aStatistics. 615 0$aStatistics$xComputer programs. 615 0$aStatistics. 615 14$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 615 24$aStatistical Theory and Methods. 615 24$aStatistical Software. 615 24$aStatistics in Business, Management, Economics, Finance, Insurance. 676 $a519.52 700 $aMorales$b Domingo$0854068 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484980203321 996 $aA course on small area estimation and mixed models$91907149 997 $aUNINA