JSM 2011 Online Program

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Abstract Details

Activity Number: 244
Type: Contributed
Date/Time: Monday, August 1, 2011 : 2:00 PM to 3:50 PM
Sponsor: Social Statistics Section
Abstract - #300634
Title: Exploring New Models for Population Prediction in Detecting Demographic Phase Change for Sparse Census Data
Author(s): Arindam Gupta*+
Companies: Burdwan University
Address: Department of Statistics, Burdwan, International, 713104, India
Keywords: Population Prediction ; Relative Growth Rate ; Demographic Phase Change

Logistic model has some limitations when applied for developing countries. In such situation the relative growth rates (RGR) exhibit some unusual trends (increasing, primary increasing and then decreasing). To tackle those situations we extend the logistic law by incorporating nonlinear positive and negative feed back terms. Here we have assumed that RGR is a function of size and time separately. The time covariate model has some key advantages than the size covariate model. It can detect the demographic phase change point at which a developing country switches over towards a developed one.

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