Abstract
In this chapter, we continue our presentation of methods which are applied directly to the likelihood or to the posterior. However, in this chapter we work with higher-order approximations to these functions. In Section 3.1, we discuss numerical integration as a method to obtain a close approximation to the marginal of the posterior or of the likelihood. Section 3.2 approaches the problem of higher-order approximations to the posterior or to the likelihood from the point of view of Laplace’s method. Section 3.3 presents the methods of Monte Carlo, importance sampling and rejection/acceptance to realize a sample from the function of interest. Iterative Monte Carlo methods are presented in chapters 5 and 6.
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© 1996 Springer-Verlag New York, Inc.
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Tanner, M.A. (1996). Nonnormal Approximations to Likelihoods and Posteriors. In: Tools for Statistical Inference. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4024-2_3
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DOI: https://doi.org/10.1007/978-1-4612-4024-2_3
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