New Partially Linear Regression and Machine Learning Models Applied to Agronomic Data

New Partially Linear Regression and Machine Learning Models Applied to Agronomic Data

Regression analysis can be appropriate to describe a nonlinear relationship between the response variable and the explanatory variables. This article describes the construction of a partially linear regression model with two systematic components based on the exponentiated odd log-logistic normal di...

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Bibliographic Details
Main Authors: Gabriela M. Rodrigues, Edwin M. M. Ortega, Gauss M. Cordeiro
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Axioms
Subjects:
agronomic experimentation
cross validation
decision tree
maximum likelihood estimation
random forest
residual analysis
Online Access:https://www.mdpi.com/2075-1680/12/11/1027

Internet

https://www.mdpi.com/2075-1680/12/11/1027

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