LEADER 02954nam 22005415 450 001 9910349347103321 005 20250327104104.0 010 $a9781493997619 010 $a1493997610 024 7 $a10.1007/978-1-4939-9761-9 035 $a(CKB)4100000008878186 035 $a(DE-He213)978-1-4939-9761-9 035 $a(MiAaPQ)EBC5920909 035 $a(PPN)258303875 035 $a(MiAaPQ)EBC31886112 035 $a(Au-PeEL)EBL31886112 035 $a(OCoLC)1114289052 035 $a(EXLCZ)994100000008878186 100 $a20190801d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 12$aA Graduate Course on Statistical Inference /$fby Bing Li, G. Jogesh Babu 205 $a1st ed. 2019. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2019. 215 $a1 online resource (XII, 379 p. 148 illus.) 225 1 $aSpringer Texts in Statistics,$x2197-4136 311 08$a9781493997596 311 08$a1493997599 327 $a1. Probability and Random Variables -- 2. Classical Theory of Estimation -- 3. Testing Hypotheses in the Presence of Nuisance Parameters -- 4. Testing Hypotheses in the Presence of Nuisance Parameters -- 5. Basic Ideas of Bayesian Methods -- 6. Bayesian Inference -- 7. Asymptotic Tools and Projections -- 8. Asymptotic Theory for Maximum Likelihood Estimation -- 9. Estimating Equations -- 10. Convolution Theorem and Asymptotic Efficiency -- 11. Asymptotic Hypothesis Test -- References -- Index. 330 $aThis textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course. 410 0$aSpringer Texts in Statistics,$x2197-4136 606 $aStatistics 606 $aStatistical Theory and Methods 615 0$aStatistics. 615 14$aStatistical Theory and Methods. 676 $a519.5 700 $aLi$b Bing$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767294 702 $aBabu$b G. Jogesh$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349347103321 996 $aA Graduate Course on Statistical Inference$92546597 997 $aUNINA