This R package covers a large range of semiparametric regression methods with time-varying coefficients using nonparametric kernel smoothing for the estimation.
You can install the released version of tvReg from CRAN with:
install.packages("tvReg")or the development version from GitHub with:
devtools::install_github("icasas/tvReg")The five basic functions in this package are tvLM(),
tvAR(), tvSURE(), tvPLM(),
tvVAR() and tvIRF(). Moreover, this package
provides the confint(), fitted(),
forecast(), plot(), predict(),
print(), resid() and summary()
methods adapted to the class attributes of the tvReg. In
addition, it includes bandwidth selection methods, time-varying
variance-covariance estimators and four estimation procedures: the
time-varying ordinary least squares, which are implemented in the
tvOLS() methods, the time-varying generalised least squares
for a list of equations, which is implemented in the
tvGLS() methods, time-varying pooled and random effects
estimators for panel data, which are implemented in the
tvRE() and the time-varying fixed effects estimator, which
is implemente in the tvFE().
Casas, Isabel and Fernandez-Casal, Ruben, tvReg: Time-varying Coefficient Linear Regression for Single and Multi-Equations in R (2022). R Journal, 14/1, pp. 79 - 100. link.