The present paper deals with nonlinear, non-monotonic data regression. This paper introduces an efficient algorithm to perform data transformation from non-monotonic to monotonic to be paired with a statistical bivariate regression method. The proposed algorithm is applied to a number of synthetic and real-world non-monotonic data sets to test its effectiveness. The proposed novel non-isotonic regression algorithm is also applied to a collection of data about strontium isotope stratigraphy and compared to a LOWESS regression tool.
A novel non-isotonic statistical bivariate regression method-application to stratigraphic data modeling and interpolation / Polucci, D.; Fiori, S.; Marchetti, M.. - In: MATHEMATICAL AND COMPUTATIONAL APPLICATIONS. - ISSN 2297-8747. - ELETTRONICO. - 25:1(2020). [10.3390/mca25010015]
A novel non-isotonic statistical bivariate regression method-application to stratigraphic data modeling and interpolation
Fiori S.
;
2020-01-01
Abstract
The present paper deals with nonlinear, non-monotonic data regression. This paper introduces an efficient algorithm to perform data transformation from non-monotonic to monotonic to be paired with a statistical bivariate regression method. The proposed algorithm is applied to a number of synthetic and real-world non-monotonic data sets to test its effectiveness. The proposed novel non-isotonic regression algorithm is also applied to a collection of data about strontium isotope stratigraphy and compared to a LOWESS regression tool.File | Dimensione | Formato | |
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