Journal of Statistical Theory and Applications

Volume 18, Issue 4, December 2019, Pages 375 - 386

Bayesian Analysis of Inverse Gaussian Stochastic Conditional Duration Model

Authors
C.G. Sri Ranganath*, N. Balakrishna
Department of Statistics, Cochin University of Science and Technology, Cochin, Kerala, 682022, India
*Corresponding author. Email: cg.srirang@gmail.com
Corresponding Author
C.G. Sri Ranganath
Received 20 September 2017, Accepted 21 October 2019, Available Online 20 November 2019.
DOI
10.2991/jsta.d.191031.001How to use a DOI?
Keywords
Stochastic conditional duration; Bayesian analysis; Markov Chain Monte Carlo; Inverse Gaussian distribution; Slice sampler
Abstract

This paper discusses Bayesian analysis of stochastic conditional duration model when the innovations follow inverse Gaussian distribution. Estimation is carried out by the methods of Markov Chain Monte Carlo. Applications of the model and methods are illustrated through simulation and data analysis.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
18 - 4
Pages
375 - 386
Publication Date
2019/11/20
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
10.2991/jsta.d.191031.001How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - C.G. Sri Ranganath
AU  - N. Balakrishna
PY  - 2019
DA  - 2019/11/20
TI  - Bayesian Analysis of Inverse Gaussian Stochastic Conditional Duration Model
JO  - Journal of Statistical Theory and Applications
SP  - 375
EP  - 386
VL  - 18
IS  - 4
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.191031.001
DO  - 10.2991/jsta.d.191031.001
ID  - SriRanganath2019
ER  -