Logistic mixtures vs. Markov chain Monte Carlo

Date of Publication

2008

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Statistics Major in Actuarial Science

Subject Categories

Statistics and Probability

College

College of Science

Department/Unit

Mathematics and Statistics

Thesis Adviser

Frumencio F. Co

Defense Panel Chair

Regina Tresvalles

Defense Panel Member

Shirlee Ocampo
Michele Tan

Abstract/Summary

Economic time series models and innovations have undergone through tremendous changes over the years, thus providing answers to some of the unsolvable problems. With regime switching time series models, simulated data is used to compare the unobserved state vector if it follows a Markov Chain Monte Carlo or a Logistic Mixture Process. By using OpenBUGS, results for Markov Chain Monte Carlo are obtained. Also, by using Statistica and EVIEWS, results for Logistic Mixture Model are obtained. AR(1) is then applied to the real data to determine the existence of regimes.;"This paper is based on the comparison of regime switching models by Paliouras (2007) entitled Comparing Regime-Switching Models in Time Series: Logistic Mixtures vs. Markov switching. "

Abstract Format

html

Language

English

Format

Print

Accession Number

TU15428

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

76 leaves, illustrations (some color), 28 cm.

Keywords

Monte Carlo method; Markov processes

Embargo Period

3-25-2021

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