Parametric Statistical Inference
by Lindsey, J. K.Format: Hardcover
Pub. Date: 1996-08-01
Publisher(s): Clarendon Press
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Summary
Inference involves drawing conclusions about some general phenomenon from limited empirical observations in the face of random variability. Two central unifying components of statistics are the likelihood function and the exponential family. These are here brought together for the firsttime as the central themes of a book on statistical inference. This book is appropriate as an advanced undergraduate or graduate text in mathematical statistics.
Table of Contents
| Model Building | |
| Model building | |
| Exponential family | |
| Inference | |
| Likelihood | |
| Goodness of it | |
| Approximations | |
| Asymptotics | |
| Factoring the likelihood function | |
| Decisions | |
| Frequentist decision-making | |
| Bayesian decision-making | |
| Examples | |
| Poisson regression | |
| Binomial regression | |
| Appendices | |
| Elements of measure theory | |
| Review of probability theory | |
| Normal distribution statistics | |
| Numerical methods | |
| Bibliography | |
| Index | |
| Table of Contents provided by Publisher. All Rights Reserved. |
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