A functional data analysis approach to the estimation of densities over complex regions
Keywords
Statistical learning
Code:
51/2020
Title:
A functional data analysis approach to the estimation of densities over complex regions
Date:
Thursday 23rd July 2020
Author(s):
Ferraccioli, F.; Sangalli, L. M.; Arnone, E.,; Finos, L.
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Abstract:
In this work we propose a nonparametric method for density estimation over two-dimensional domains. Following a functional data analysis approach, we consider a penalized likelihood estimator, with a roughness penalty based on a differential operator. This approach allows for the estimation of densities on any planar domain, including those with complex boundaries or interior holes. We develop an estimation procedure based on fi nite elements. Thanks to the use of this numerical technique, the proposed method has great flexibility and high computational efficiency.
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Ferraccioli, F., Sangalli, L. M., Arnone, E., & Finos, L. (2020, June). A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions. In International Workshop on Functional and Operatorial Statistics (pp. 77-82). Springer, Cham.
Ferraccioli, F., Sangalli, L. M., Arnone, E., & Finos, L. (2020, June). A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions. In International Workshop on Functional and Operatorial Statistics (pp. 77-82). Springer, Cham.