A Model for Age-Specific Fertility Rate Pattern of India Using Skew-Logistic Distribution Function
American Journal of Theoretical and Applied Statistics
Volume 6, Issue 1, January 2017, Pages: 32-37
Received: Dec. 26, 2016; Accepted: Jan. 6, 2017; Published: Feb. 3, 2017
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Authors
Ruchi Mishra, Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India
Kaushalendra Kumar Singh, Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India
Anjali Singh, Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India
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Abstract
Fertility governs central and positive role in the study of human population dynamics. The age-specific fertility pattern has a distinct shape for all human population, to describe which, a number of parametric models have been proposed. The purpose of this study is to develop a mathematical model for fitting age-specific fertility rate pattern of various states of India. Skew-logistic probability density function is used for building the model. The real data, to which this model has been fitted, is obtained from National Family Health Survey- III (2005-2006). The used model is very flexible in nature and hence is useful for modeling diverse fertility patterns which are observed across different states of India. The parameters of the model have been estimated through the method of non-linear least square. By fitting the model it is observed that the proposed model fits well on the fertility pattern for almost each state of the country.
Keywords
Age-Specific Fertility Rate, Parametric Model, Skew-Logistic Probability Density Function, Non-Linear Least Square
To cite this article
Ruchi Mishra, Kaushalendra Kumar Singh, Anjali Singh, A Model for Age-Specific Fertility Rate Pattern of India Using Skew-Logistic Distribution Function, American Journal of Theoretical and Applied Statistics. Vol. 6, No. 1, 2017, pp. 32-37. doi: 10.11648/j.ajtas.20170601.14
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Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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