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Cubic splines are commonly used for capturing the changes in economic analysis. This is because of the fact that traditional regression including polynomial regression fail to capture the underlying changes in the corresponding response variables. Moreover, these variables do not change monotonically, i.e. there are discontinuities in the trend of these variables over a period of time. The objective of this research is to explain the movement of under-five child mortality in Pakistan over the past few decades through a combination of statistical techniques. While cubic splines explain the movement of under-five child mortality to a large extent, we cannot deny the possibility that splines with fractional powers might better explain the underlying movement. . Hence, we estimated the value of fractional power by nonlinear regression method and used it to develop the fractional splines. Although, the fractional spline model may have the potential to improve upon the cubic spline model, it does not demonstrate a real improvement in results of this case, but, perhaps, with a different data set.
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How to Cite
Esar, S. E., Kamal, S. K., & Sherwani, R. A. K. (2017). Comparison of fractional splines with polynomial splines; An Application on under-five year’s child mortality data in Pakistan (1960-2012). Pakistan Journal of Statistics and Operation Research, 13(2), 439-448. https://doi.org/10.18187/pjsor.v13i2.1841