This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog
Maximum Likelihood Estimation and Inference (With Examples in R, SAS and ADMB) || Fundamental Paradigms and Principles of Inference
โ Scribed by Millar, Russell B.
- Book ID
- 101396313
- Publisher
- John Wiley & Sons, Ltd
- Year
- 2011
- Tongue
- English
- Weight
- 140 KB
- Edition
- 1
- Category
- Article
- ISBN
- 0470094826
No coin nor oath required. For personal study only.
โฆ Synopsis
Fundamental paradigms and principles of inference
The statistician cannot excuse himself from the duty of getting his head clear on the principles of scientific inference, but equally no other thinking man can avoid a like obligation -Sir Ronald Fisher 1 See Section 15.3 for a quick self-test of frequentist versus Bayesian thinking.
๐ SIMILAR VOLUMES
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog