CSmoothing: a web-tool for controlled smoothing by segments of mortality data

Abstract

CSmoothing allows an analyst to use the so-called Controlled Smoothing technique to estimate trends in a time series framework. In this Web-tool (Shiny), the analyst may apply the methodology to at most 3 mortality time series simultaneously, as well as to other kind of time series individually. Likewise, this smoothing approach allows the analyst to establish one, two or three segments in order to take into account possible changes in variance regimes. For estimating trends it uses different amounts of smoothness, both globally for the total data set and through some partial indices for each selected segment. It is also possible to endogenously fix the points where the segments start and end (the cutoff points) with continuous joints. Additionally, intervals of different standard deviations for their respective trends are given. Particular emphasis is placed on a big data set of log mortality rates, log(qx), taken from period life tables of the Human Mortality Database (HMD) (University of California Berkeley (USA) and and Max Planck Institute for Demographic Research (Germany)), 2021). In all cases, dynamic graphs and several statistics related to the Controlled Smoothing technique are illustrated.