Bayes analysis of abridged age specific fertility pattern using parametric models

The paper provides a Bayesian alternative to transform the abridged age-specific fertility data into an unabridged one. A model suitable for a binary type of fertility data is considered for the study. The success probabilities of the considered model are assumed to vary in accordance with some esta...

Full description

Saved in:
Bibliographic Details
Published in:Communications in statistics. Theory and methods 2022-08, Vol.51 (16), p.5505-5533
Main Authors: Mishra, Rahul Kumar, Upadhyay, Satyanshu K.
Format: Article
Language:English
Subjects:
Age
Age-specific fertility rate
Algorithms
Bayes analysis
Bayes information criterion
Bayesian analysis
Fertility
Gibbs sampler
Grouped data
Metropolis-Hastings algorithm
Model comparison
Non-linear model
Parametric statistics
Predictive loss criterion
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The paper provides a Bayesian alternative to transform the abridged age-specific fertility data into an unabridged one. A model suitable for a binary type of fertility data is considered for the study. The success probabilities of the considered model are assumed to vary in accordance with some established parametric age-specific fertility models. Bayes analysis is done using uniform priors for the unknown parameters of the considered models. Since the posterior analysis involves analytically intractable form of integrals, the paper employs the Gibbs sampler algorithm with intermediate Metropolis-Hastings steps to draw the corresponding posterior samples. Numerical illustration is provided using grouped age-specific fertility rate data. Finally, a few standard Bayesian model comparison tools are used in order to recommend an appropriate model for the data in hand, keeping in view the intended objectives.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2020.1843052