Piece wise regression for atmospheric data

There are numerous regression models in literature and some of them are simple linear, multiple linear, polynomial, Cubic, Stepwise, Ridge, Lasso, Elastic Net, Negative Binomial, Poisson, Partial, Principal Component Regression etc. Generally regression gives single fit for total data. Splines or pi...

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Bibliographic Details
Main Authors: Reddy, S. Venkatramana, Damodharan, S., Kumar, K. Anil, Reddy, N. Konda, Sarojamma, B.
Format: Conference Proceeding
Language:English
Subjects:
Atmospheric models
Polynomials
Regression models
Spline functions
Online Access:Get full text
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Summary:There are numerous regression models in literature and some of them are simple linear, multiple linear, polynomial, Cubic, Stepwise, Ridge, Lasso, Elastic Net, Negative Binomial, Poisson, Partial, Principal Component Regression etc. Generally regression gives single fit for total data. Splines or piecewise regression gives two or more regression lines for data using knots. In this paper we are fitting trigonometric piecewise regression, Polynomial piecewise regression and cubic piecewise regression for Atmospheric data. Best among these three piecewise models is estimated using R square criteria.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0143314