Estimating normalizing constants using stochastic simulation

Bachelor Thesis (2023)
Author(s)

R.M. Hallema (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

G.N.J.C. Bierkens – Mentor (TU Delft - Statistics)

Y. van Gennip – Graduation committee member (TU Delft - Mathematical Physics)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Rinze Hallema
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Rinze Hallema
Graduation Date
23-06-2023
Awarding Institution
Delft University of Technology
Project
['AM3000']
Programme
['Applied Mathematics']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

The computation of normalizing constants often brings (higher-dimensional) integrals, which could not be computed analytically or are computationally expensive. Stochastic methods will be explored to find an estimate for normalizing constants. These stochastic methods will be used to estimate the Bayes factor. With this Bayes factor can be searched for a best fitting model to data.

Files

BEP_Rinze_Hallema_1_1_.pdf
(pdf | 1.52 Mb)
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