tvCoef

The goal of tvCoef is to study time-varying coefficients models around linear regression:

• piecewise regressions (using strucchange to detect the break dates) ;

• local regressions (using tvReg) ;

• state space models (using rjd3sts).

Installation

tvCoef relies on rjd3sts which need Java JRE 17 or later version.

To get the current stable version (from the latest release):

# install.packages("remotes")remotes::install_github("InseeFrLab/tvCoef@*release")

To get the current development version from GitHub:

# install.packages("remotes")remotes::install_github("InseeFrLab/tvCoef")
# or using r-universe:
install.packages('tvCoef', repos= c('https://aqlt.r-universe.dev', 'https://cloud.r-project.org'))

If you have troubles installing Java, check the installation manual.

Usage

library(tvCoef)
data_gdp<- window(gdp, start=1980, end= c(2019, 4))
reg_lin<- lm(
formula=growth_gdp~bc_fr_m1+diff_bc_fr_m1,
data=data_gdp
)
reg_lin#> #> Call:#> lm(formula = growth_gdp ~ bc_fr_m1 + diff_bc_fr_m1, data = data_gdp)#> #> Coefficients:#> (Intercept) bc_fr_m1 diff_bc_fr_m1 #> -1.60008 0.02047 0.04423

ssm<- ssm_lm(
reg_lin, # To estimate the variance of the coefficient of the intercept fixed_var_intercept=FALSE, var_intercept=0.01,
# To estimate the variance of the explanatory variable fixed_var_variables=FALSE, var_variables=0.01)
ssm#> Mean of time-varying estimated coefficients (smoothing): #> (Intercept) bc_fr_m1 diff_bc_fr_m1 noise #> -1.6194 0.0207 0.0425 0.0000

summary(ssm)
#> Summary of time-varying estimated coefficients (smoothing): #> (Intercept) bc_fr_m1 diff_bc_fr_m1 noise#> Min. -1.791 0.02069 0.01972 -1.425e+00#> 1st Qu. -1.745 0.02069 0.02480 -1.997e-01#> Median -1.572 0.02069 0.04388 1.565e-02#> Mean -1.619 0.02069 0.04247 1.643e-16#> 3rd Qu. -1.518 0.02069 0.05731 2.243e-01#> Max. -1.492 0.02069 0.07697 8.114e-01

For more details on the methods, see the associated article available at https://github.com/InseeFrLab/DT-tvcoef.