Comparing Smoothing Techniques on Fertility Data
Javier M. Moguerza, Alberto Olivares, Anastasia Kostaki, Stelios Psarakis · 2010
This paper compares different smoothing techniques for graduating fertility rates. In particular we focus on some well-known parametric models, standard non-parametric statistical methods such as kernels and splines, and Support Vector Machines (SVM). In this work, we apply these techniques to empirical age-specific fertility rates from a variety of populations and time periods.