protocol
发表于 2025-3-21 16:26:48
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ADORE
发表于 2025-3-21 21:34:16
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主讲人
发表于 2025-3-22 03:50:20
Textbook 2020Latest editionimportance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wal
花束
发表于 2025-3-22 08:03:56
1431-8776medicine and epidemiology with programming examples in the This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of
abject
发表于 2025-3-22 10:40:39
Likelihood,tion, and Fisher information. Computational algorithms are treated to compute the maximum likelihood estimate, such as optimisation and the EM algorithm. The concept of sufficiency and the likelihood principle are finally discussed in some detail. Exercises are given at the end.
Visual-Acuity
发表于 2025-3-22 15:10:57
Frequentist Properties of the Likelihood,the corresponding confidence intervals are introduced. Variance-stabilising transformations are also discussed. A case study comparing coverage and width of several confidence intervals for a proportion finishes this chapter, completed by a number of exercises at the end.
Tracheotomy
发表于 2025-3-22 20:48:26
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使尴尬
发表于 2025-3-22 21:59:23
Model Selection,its connection to cross-validation. Bayesian model selection based on the marginal likelihood is described, including Bayesian model averaging. Finally, DIC is introduced, completed by a number of exercises at the end.
竞选运动
发表于 2025-3-23 03:09:55
Numerical Methods for Bayesian Inference, provide ways to numerically compute posterior characteristics of interest. Monte Carlo methods, including Monte Carlo integration, rejection and importance sampling as well as Markov chain Monte Carlo are described. Finally, numerical computation of the marginal likelihood, necessary for Bayesian m
杀人
发表于 2025-3-23 05:46:15
Prediction, predictions, obtained with either a likelihood or Bayesian approach. Connections to the simpler plug-in prediction are also described. Finally, methods to assess the quality of probabilistic predictions, such as the Brier and the logarithmic score, are described. Exercises are given at the end.