Journal of Statistical Theory and Applications

Volume 18, Issue 4, December 2019, Pages 450 - 463

Analysis of Count Data by Transmuted Geometric Distribution

Authors
Subrata Chakraborty1, Deepesh Bhati2, *
1 Department of Statistics, Dibrugarh University, Assam, India
2 Department of Statistics, Central University of Rajasthan, Rajasthan, India
*Corresponding author. Email: deepesh.bhati@curaj.ac.in
Corresponding Author
Deepesh Bhati
Received 30 November 2017, Accepted 14 September 2018, Available Online 27 December 2019.
DOI
https://doi.org/10.2991/jsta.d.191218.001How to use a DOI?
Keywords
Transmuted geometric distribution, EM algorithm, Likelihood Ratio test, Rao score's test, Wald's test
Abstract

Transmuted geometric distribution (TGD) was recently introduced and investigated by Chakraborty and Bhati [Stat. Oper. Res. Trans. 40 (2016), 153–176]. This is a flexible extension of geometric distribution having an additional parameter that determines its zero inflation as well as the tail length. In the present article we further study this distribution for some of its reliability, stochastic ordering and parameter estimation properties. In parameter estimation among others we discuss an EM algorithm and the performance of estimators is evaluated through extensive simulation. For assessing the statistical significance of additional parameter α, Likelihood ratio test, the Rao's score tests and the Wald's test are developed and its empirical power via simulation are compared. We have demonstrate two applications of (TGD) in modeling real life count data.

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
450 - 463
Publication Date
2019/12
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
https://doi.org/10.2991/jsta.d.191218.001How 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  - Subrata Chakraborty
AU  - Deepesh Bhati
PY  - 2019
DA  - 2019/12
TI  - Analysis of Count Data by Transmuted Geometric Distribution
JO  - Journal of Statistical Theory and Applications
SP  - 450
EP  - 463
VL  - 18
IS  - 4
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.191218.001
DO  - https://doi.org/10.2991/jsta.d.191218.001
ID  - Chakraborty2019
ER  -