Statistical inference in partial linear regression models
Description
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.