00949nam 2200253la 450 991048206550332120221108055334.0(UK-CbPIL)2090316757(CKB)5500000000088517(EXLCZ)99550000000008851720210618d1699 uy |laturcn||||a|bb|Dissertatio theologica inauguralis de angelo satan colaphizante Paulum, ad 2 Cor. XII. 7.-fPetrus Santvoort[electronic resource]Leiden Abraham Elzevir1699Online resource (.. p, 8°)Reproduction of original in Koninklijke Bibliotheek, Nationale bibliotheek van Nederland.Santvoort Petrus929868Uk-CbPILUk-CbPILBOOK9910482065503321Dissertatio theologica inauguralis de angelo satan colaphizante Paulum, ad 2 Cor. XII. 7.-fPetrus Santvoort2090794UNINA02954nam 22005415 450 991034934710332120250327104104.09781493997619149399761010.1007/978-1-4939-9761-9(CKB)4100000008878186(DE-He213)978-1-4939-9761-9(MiAaPQ)EBC5920909(PPN)258303875(MiAaPQ)EBC31886112(Au-PeEL)EBL31886112(OCoLC)1114289052(EXLCZ)99410000000887818620190801d2019 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierA Graduate Course on Statistical Inference /by Bing Li, G. Jogesh Babu1st ed. 2019.New York, NY :Springer New York :Imprint: Springer,2019.1 online resource (XII, 379 p. 148 illus.) Springer Texts in Statistics,2197-41369781493997596 1493997599 1. 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.This 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.Springer Texts in Statistics,2197-4136StatisticsStatistical Theory and MethodsStatistics.Statistical Theory and Methods.519.5Li Bingauthttp://id.loc.gov/vocabulary/relators/aut767294Babu G. Jogeshauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910349347103321A Graduate Course on Statistical Inference2546597UNINA