In All Likelihood
by Yudi Pawitan · first published 2001
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2017–2023first – last mentioned
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This book presents the role of likelihood in a whole range of statistical problems, from a simple comparison of two accident rates to complex studies requiring generalized linear or semiparametric modeling. The book emphasizes that the likelihood is not simply a device to produce an estimate, but more importantly it is a tool for modeling. The book generally takes an informal approach, where most important results are established using heuristic arguments and motivated with realistic examples. With currently available computing power, examples are not contrived to allow a closed analytical
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…Fisher school's of thought which is a half way point or a can be seen as a compromise between Frequentist and Bayesian approach. A good book that talk about this which I've been meaning to read is... In All Likelihood: Statistical Modelling and Inference Using Likelihood by Yudi Pawitan. I've read the first chapter and it's a very interesting read. I might skip bayes and go straight to likelihood coming from the school…
on “Statistical Thinking: My Journey from Frequentist to Bayesian Statistics” ↗> A good book that talk about this which I've been meaning to read is... In All Likelihood: Statistical Modelling and Inference Using Likelihood by Yudi Pawitan. It's good but it's mostly a technical introduction to statistical inference (i.e. the mathematics that make statistics work), and…
on “Statistical Thinking: My Journey from Frequentist to Bayesian Statistics” ↗My grind was "Mathematical Statistics with Applications" by Wackerly et al. There are PDF versions if you Google for it. I can't say it was quick, easy or intuitive; but it works. I also liked "In all Likelihood" by Pawitan for a "likelihoodist" foundational approach.
on “Introduction to Modern Statistics” ↗