Cargando…
A parametric framework for multidimensional linear measurement error regression
The ordinary linear regression method is limited to bivariate data because it is based on the Cartesian representation y = f(x). Using the chain rule, we transform the method to the parametric representation (x(t), y(t)) and obtain a linear regression framework in which the weighted average is used...
Autor principal: | Luck, Stanley |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782541/ https://www.ncbi.nlm.nih.gov/pubmed/35061791 http://dx.doi.org/10.1371/journal.pone.0262148 |
Ejemplares similares
-
A method for detecting outliers in linear-circular non-parametric regression
por: Sert, Sümeyra, et al.
Publicado: (2023) -
Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat
por: Pérez-Rodríguez, Paulino, et al.
Publicado: (2012) -
Statistical regression with measurement error
por: Cheng, Chi-Lun, et al.
Publicado: (1999) -
Phase Unwrapping Error Correction Based on Multiple Linear Regression Analysis
por: Lv, Zhuang, et al.
Publicado: (2023) -
Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships
por: Kudryashova, Nina, et al.
Publicado: (2022)