00000caa a22000003i 4500 UP-1685594773862408735 Buklod 20210411213227.0 m | | ta 210411s2020 xx r |||| u|eng d (iLib)UPBAG-00039679897 STII-DOST BAG rda eng ARTICLE-3060 Manejero, James Lee author. Variational approach to data graduation by James Lee Manejero and Renier Mendoza. 2020. pages 423-441 color illustrations 26 cm text rdacontent unmediated rdamedia volume rdacarrier Includes bibliographical references (pages 440-441) The Whittaker-Henderson graduation is a data smoothing method commonly used in actuarial science for mortality table computation. This method is a finite-dimensional minimization problem, which aims to give a smooth approximation of the crude data. Our goal is to treat the Whittaker-Henderson method as a minimization problem in a Sobolev space. We take advantage of some results in the study of Sobolev spaces to analyze the solution to the graduation problem. Solving the arising minimization problem is equivalent to solving a partial differential equation (PDE). To solve the PDE numerically, we use the finite element method (FEM). We apply this variational approach to the data sets found in the literature. In particular, we test our method to check for patterns in (1) mortality rates for Filipino males, (2) global average temperature anomaly, and (3) monthly eBay share price. We also compare the results with that of the Whittaker-Henderson method. (Author's abstract) Mathematics. Finite element method. Optimization. Variational formulation. Whittaker-henderson graduation method. Mendoza, Renier author. The Philippine Journal of Science Vol. 149, no. 2, June 2020. Request full-text access via UPB University Library through https://forms.gle/KZjBv7aRtY6jiL5E9 (viewed 11 April 2021) FI UPBAG UPBAG-MAIN ARTICLE-3060 Analytics