Generalized Quasilikelihood Inference for Zero Inflated Longitudinal Count Data

Authors

  • Jannatul Ferdous Antu Department of Statistics, University of Dhaka, Dhaka-1000, Bangladesh
  • Sabina Sharmin Department of Statistics, University of Dhaka, Dhaka-1000, Bangladesh
  • Taslim Sazzad Mallick Department of Statistics, University of Dhaka, Dhaka-1000, Bangladesh

DOI:

https://doi.org/10.3329/dujs.v68i1.54602

Keywords:

Longitudinal data, Zero inflation, Inference, Quasilikelihood, Generalized Quasilikelihood

Abstract

In this paper, we extend an observation-driven model for time series of zero inflated count data to longitudinal data setup. Basic properties of the models are discussed. For statistical inference of the proposed model, a generalized quasilikelihood (GQL) estimating equation has been derived for the regression parameter. A pharmaceutical data has been reanalyzed using the proposed approach and results are compared. The proposed approach produces similar estimates as given in the earlier work with much smaller standard errors.

Dhaka Univ. J. Sci. 68(1): 95-99, 2020 (January)

Downloads

Download data is not yet available.
Abstract
29
PDF
37

Downloads

Published

2020-01-30

How to Cite

Antu, J. F., Sharmin, S., & Mallick, T. S. (2020). Generalized Quasilikelihood Inference for Zero Inflated Longitudinal Count Data. Dhaka University Journal of Science, 68(1), 95–99. https://doi.org/10.3329/dujs.v68i1.54602

Issue

Vol. 68 No. 1 (2020)

Section

Articles