Journal of Siberian Federal University. Engineering & Technologies: Piecewise Polynomial Models for Aggregation and Regression Analysis in Remote Sensing of the Earth Problems

Journal of Siberian Federal University. Engineering & Technologies / Piecewise Polynomial Models for Aggregation and Regression Analysis in Remote Sensing of the Earth Problems

Issue: Journal of Siberian Federal University. Engineering & Technologies. 2018 11 (8)
Authors: Popova, Olga A.
Contact information: Popova, Olga A.: Siberian Federal University 79 Svobodny, Krasnoyarsk, 660041, Russia;
Keywords: numerical probabilistic analysis; data aggregation; regression modeling; piecewise polynomial model; density function
Abstract: We discuss the procedures of data aggregation as a preprocessing stage for subsequent to regression modeling. An important feature of study is demonstration of the way how represent the aggregated data. It is proposed to use piecewise polynomial models, including spline aggregate functions. We show that the proposed approach to data aggregation can be interpreted as the frequency distribution. To study its properties density function concept is used. Applying data aggregation models as input and output variables we propose a new probability density function value linear regression model (Distributions Regression). To calculate the data aggregation and regression model we employ numerical probabilistic analysis (NPA). To demonstrate the degree of the correspondence of the proposed methods to reality, we developed a theoretical framework and considered numerical examples
Pages: 964-973
Paper at repository of SibFU: https://elib.sfu-kras.ru/handle/2311/109199