Download Bayesian estimation of state-space models using the by Geweke J., Tanizaki H. PDF

By Geweke J., Tanizaki H.

During this paper, an try is made to teach a basic approach to nonlinear and/or non-Gaussian state-space modeling in a Bayesian framework, which corresponds to an extension of Carlin et al. (J. Amer. Statist. Assoc. 87(418} (1992) 493-500) and Carter and Kohn (Biometrika 81(3} (1994) 541-553; Biometrika 83(3) (1996) 589-601). utilizing the Gibbs sampler and the Metropolis-Hastings set of rules, an asymptotically certain estimate of the smoothing suggest is bought from any nonlinear and/or non-Gaussian version. furthermore, taking numerous applicants of the thought density functionality, we study precision of the proposed Bayes estimator.

Show description

Read or Download Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling PDF

Similar algorithms and data structures books

Algorithm Theory — SWAT'98: 6th Scandinavian Workshop on Algorithm Theory Stockholm, Sweden, July 8–10, 1998 Proceedings

This booklet constitutes the refereed court cases of the sixth Scandinavian Workshop on set of rules thought, SWAT'98, held in Stockholm, Sweden, in July 1998. the amount offers 28 revised complete papers chosen from fifty six submissions; additionally integrated are 3 invited contributions. The papers current unique study on algorithms and information buildings in a variety of parts together with computational geometry, parallel and allotted structures, graph thought, approximation, computational biology, queueing, Voronoi diagrams, and combinatorics regularly.

Robust range image registration: using genetic algorithms and the surface interpenetration measure

This publication addresses the variety photograph registration challenge for automated 3D version development. the focal point is on acquiring hugely specified alignments among diversified view pairs of an identical item to prevent 3D version distortions; unlike such a lot previous paintings, the view pairs may perhaps convey fairly little overlap and needn't be prealigned.

A Recursive Introduction to the Theory of Computation

The purpose of this textbook is to offer an account of the speculation of computation. After introducing the concept that of a version of computation and proposing numerous examples, the writer explores the restrictions of powerful computation through easy recursion concept. Self-reference and different tools are brought as basic and uncomplicated instruments for developing and manipulating algorithms.

Extra info for Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling

Sample text

5. 6. Some simple computations Some simple architectures Algorithms for a linear array Algorithms for a binary tree Algorithms for a 2D mesh Algorithms with shared variables 25 This page intentionally left blank. 1. SOME SIMPLE COMPUTATIONS In this section, we define five fundamental building-block computations: 1. 2. 3. 4. 5. Semigroup (reduction, fan-in) computation Parallel prefix computation Packet routing Broadcasting, and its more general version, multicasting Sorting records in ascending/descending order of their keys Semigroup Computation.

For example, if P 0 is holding (1, 3, 7, 8) and P 1 has (2, 4, 5, 9), a merge–split step will turn the lists into (1, 2, 3, 4) and (5, 7, 8, 9), respectively. Because the sublists are sorted, the merge–split step requires n/p compare–exchange steps. Thus, the total time of the algorithm is (n/p)log2 (n /p ) + n . Note that the first term (local sorting) will be dominant if p < log 2 n, while the second term (array merging) is dominant for p > log2 n . For p ≥ log 2 n, the time complexity of the algorithm is linear in n; hence, the algorithm is more efficient than the one-key-per-processor version.

For p ≥ log 2 n, the time complexity of the algorithm is linear in n; hence, the algorithm is more efficient than the one-key-per-processor version. One final observation about sorting: Sorting is important in its own right, but occasionally it also helps us in data routing. Suppose data values being held by the p processors of a linear array are to be routed to other processors, such that the destination of each value is different from all others. This is known as a permutation routing problem.

Download PDF sample

Rated 4.15 of 5 – based on 28 votes