Stochastic Analysis of Infant Deaths by Age and Estimation of Parameters


  • Brijesh P. Singh Faculty of Commerce & DST-Centre for Interdisciplinary Mathematical Sciences, Baranas Hindu University
  • Shweta Dixit Department of Statistics, Baranas Hindu University
  • Tapan Kumar Roy Department of Population Studies & HRD, Rajshahi University



Infant death, probability models, maximum likelihood, Bayesian estimation


Infant Mortality Rate (IMR) is a sensitive and powerful index of development. Birth and death, registered through vital registration system in the developing countries suffer from age misreporting, omissions and under count. To overcome this defectiveness in data and to obtain reliable estimates of birth and death rates, India introduced Sample Registration System (SRS) in 1960 but still they suffer from considerable degree of errors. It is observed in retrospective surveys that events are misreported due to ignorance and digit preference of the respondents. Thus, the data on deaths collected, suffer from one defect or other as mentioned above. To resolve this problem attempts have been made to develop and fit suitable models to data on age distribution of deaths. In this paper an attempt has been made to develop a model with an idea of the majority of infant deaths occurs within the first month of their life. The model is used to give a functional shape to the phenomenon of infant deaths distribution and apply on real data taken from NFHS.

Journal of Institute of Science and Technology, 2015, 20(1): 1-5


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How to Cite

Singh, B. P., Dixit, S., & Roy, T. K. (2015). Stochastic Analysis of Infant Deaths by Age and Estimation of Parameters. Journal of Institute of Science and Technology, 20(1), 1–5.



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