z-logo
open-access-imgOpen Access
Bayesian analysis to detect change-point in two-phase Laplace model
Author(s) -
A. Jafari,
Masoud Yarmohammadi,
Aliakbar Rasekhi
Publication year - 2016
Publication title -
scientific research and essays
Language(s) - English
Resource type - Journals
ISSN - 1992-2248
DOI - 10.5897/sre2016.6441
Subject(s) - laplace transform , bayesian probability , point (geometry) , computer science , phase change , mathematics , physics , artificial intelligence , mathematical analysis , thermodynamics , geometry
The general form of the change-point problem is to determine the unknown location , based on an ordered sequence of observations such that, the two groups of observation and follow distinct models. In this paper the problem of changepoint detection of two-phase Laplace model is considered. Our object is to find the location of random variables where the parameters of their model are changed. The Bayesian method is used to estimate the parameters. Then by simulation studies, the implementation of proposed method will be discussed. For estimate the parameters of the model, and the procedure of the change-point detection the R2OpenBUGS Package in R is used. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom