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