A Graduate Course on Statistical Inference, 1st ed. 2019 Springer Texts in Statistics Series
Auteurs : Li Bing, Babu G. Jogesh
Adapts to a one-semester or two-semester graduate course in statistical inference
Employs similar conditions throughout to unify the volume and clarify theory and methodology
Reflects up-to-date statistical research
Draws upon three main themes: finite-sample theory, asymptotic theory, and Bayesian statistics
Date de parution : 08-2019
Ouvrage de 379 p.
15.5x23.5 cm
Thème d’A Graduate Course on Statistical Inference :
Mots-clés :
Bayes; Bayesian; Cauchy-Schwarz; statistical inference; statistical estimation; finite-sample estimation; differentiable under the integral sign; stochastic equicontinuity; finite-sample theory; asymptotic theory; posterior distributions; empirical Bayes; shrinkage estimates; Le Cam-Hajek; estimating equations; generalized linear models; quasi-likelihood estimation; conditional inference; Local Asymptotic Normal