PLRModels: Statistical inference in partial linear regression models

This package provides statistical inference tools applied to Partial Linear Regression (PLR) models. Specifically, point estimation, confidence intervals estimation, bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. Kernel-based methods, combined with ordinary least squares estimation, are used and time series errors are allowed. In addition, these techniques are also implemented for both parametric (linear) and nonparametric regression models.

AuthorGerman Aneiros Perez and Ana Lopez Cheda
Date of publication2014-01-01 21:37:58
MaintainerGerman Aneiros Perez <>

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