Titlebook: Applied Statistical Inference; Likelihood and Bayes Leonhard Held,Daniel Sabanés Bové Textbook 20141st edition Springer-Verlag Berlin Heide

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Elements of Frequentist Inference,This chapter discusses fundamental concepts of frequentist inference, such as unbiasedness and consistency, standard errors and confidence intervals, significance tests and P-values. There is also a section on the bootstrap method. Exercises are given at the end.

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Likelihood Inference in Multiparameter Models,The concepts described in Chap. . are now extended to multiparameter models. The concept of profile likelihood is introduced as well as the generalized likelihood ratio statistic. The conditional likelihood, an alternative way to eliminate a nuisance parameter, is discussed. Exercises are given at the end.

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Bayesian Inference,ian point and interval estimates. Bayesian inference in multiparameter models is discussed and some results from Bayesian asymptotics are described. Finally, empirical Bayes methods are described, completed by a number of exercises at the end.

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