Pub. online:24 May 2024Type:Computing In Data ScienceOpen Access
Journal:Journal of Data Science
Volume 22, Issue 2 (2024): Special Issue: 2023 Symposium on Data Science and Statistics (SDSS): “Inquire, Investigate, Implement, Innovate”, pp. 208–220
Abstract
With the growing scale of big datasets, fitting novel statistical models on larger-than-memory datasets becomes correspondingly challenging. This document outlines the development and use of an API for large scale modelling, with a demonstration given by the proof of concept platform largescaler, developed specifically for the development of statistical models for big datasets.
Social phenomena that are related to human beings cannot be performed under controlled conditions, making it difficult for policy planners to have an idea about the expected future conditions in the society under varying situations and forming policies. However, modelling can be really helpful to planners in these situations. The present paper attempts to find the distributions of age at last conception of women with the help of stochastic modelling for human fertility taking into consideration different parity progression behaviours among couples. This may be helpful to planners for having at least a rough idea of estimated proportion of women of different age groups who will be completing their childbearing and willing to go for sterilization after marriage under different stopping rules regarding desired family size and sex composition of children. Accordingly, these estimates will help planners to optimize the cost and service provision for sterilization programs for women.