Book chapter
A BAYESIAN MONTE CARLO INTEGRATION STRATEGY FOR CONNECTING STOCHASTIC MODELS OF HIV/AIDS WITH DATA
Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention
01 Jan 2005
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Whenever a Bayesian procedure that involves the numerical evaluation of multi-dimensional integrals is contemplated, a decision as to whether proceed with a computer implementation of the procedure will often depend on the ease with which the software may be written. The ease with which the software may be written will, in turn, depend not only programming language chosen but also a programmer's knowledge of the language. Because the author has had rather extensive experience in using the programming language, APL, which, among other things, is known for ease with which succinct code may be written to process complex arrays, it was known at the outset that the software to program Bayesian structure outlined in this paper could written and validated with relative ease. Furthermore, it seems likely that any other programming language with array processing capabilities could also be used to write code the implement the ideas presented in this paper. Consequently, a decision was made to organize the ideas in a precise mathematical form as a first step to writing computer code in any programming language chosen by an investigator. One of the outstanding problems in using the Bayesian paradigm to estimate unknown parameters and make statistical inferences, using stochastic models of HIV/AIDS epidemics, was that of developing a methodology for drawing sample from the joint conditional posterior distribution of the parameters and the stochastic process, given the data. Chapter 6 in the recent book by (Tan, 2000) may be consulted for technical details. Among other things, this paper contains a novel procedure, depending on the ease with which large arrays may be processed in a computer, for drawing random samples from the posterior of the parameters and the process, given a sample of data.
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Details
- Title
- A BAYESIAN MONTE CARLO INTEGRATION STRATEGY FOR CONNECTING STOCHASTIC MODELS OF HIV/AIDS WITH DATA
- Creators
- Charles J. Mode
- Publication Details
- Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention
- Publisher
- World Scientific; SINGAPORE
- Number of pages
- 16
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:000300909900003
- Scopus ID
- 2-s2.0-84858322374
- Other Identifier
- 991019168807404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Infectious Diseases
- Mathematical & Computational Biology
- Mathematics, Applied
- Public, Environmental & Occupational Health