Saddlepoint approximations with applications
Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer. Written from the user's point of view, this book explains in clear language how such approximate probability computations are made, taking reader...
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| Format: | eBook |
| Language: | English |
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Cambridge
Cambridge University Press
2007
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| Series: | Cambridge series on statistical and probabilistic mathematics
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| Online Access: | |
| Collection: | Cambridge Books Online - Collection details see MPG.ReNa |
Table of Contents:
- Fundamental approximations
- Properties and derivations
- Multivariate densities
- Conditional densities and distribution functions
- Exponential families and tilted distributions
- Further exponential family examples and theory
- Probability computation with p*
- Probabilities with r*-type approximations
- Nuisance parameters
- Sequential saddlepoint applications
- Applications to multivariate testing
- Ratios and roots of estimating equations
- First passge and time to event distributions
- Bootstrapping in the transform domain
- Bayesian applications
- Nonnormal bases