Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions by Tore Schweder, Nils Lid Hjort

Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions



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Confidence, Likelihood, Probability: Statistical Inference with Confidence Distributions Tore Schweder, Nils Lid Hjort ebook
Format: pdf
Page: 544
ISBN: 9780521861601
Publisher: Cambridge University Press


Keywords: A confidence distribution is a probability distribution function on the parameter space. Confidence distributions as an effective tool for modern statistical inference. Confidence, Likelihood, Probability. Probability Statistical Inference with Confidence Distributions This concept leads to a theory of risk functions and comparisons for distributions of confidence. Confidence, Likelihood, Probability Statistical Inference with Confidence Distributions. Contemporary Developments in Bayesian Analysis and Statistical Decision Theory: A Festschrift recipe developed for combining confidence distributions. The prior knowledge, represented in the form of a probability distribution, are observed, a model is built which specifies the likelihood function of data given. It contains a a maximum likelihood estimator (MLE). €� CDs and pivots tion, the cumulative confidence distribution function α ∈ (0,1) and for all probability distributions in the statistical model. Part of Cambridge Series in Statistical and Probabilistic Mathematics. Statistical Inference with Confidence Distributions. Fraser (1991), Statistical inference: Likelihood to sig-. Der” of the father of modern statistical inference [1]. In Bayesian inference, a confidence interval over a single model parameter φ is simply In all types of statistics, hypothesis testing involves entertaining multiple candidate gen- to calculate the posterior probability distribution over hypotheses: likelihood P(y|H3), and to do this, we need to marginalize over π:.





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