Extract the parameter covariance matrix of a JVN model
Usage
# S3 method for class 'jvn_model'
vcov(object, ...)See also
Other revision nowcasting:
coef.jvn_model(),
coef.kk_model(),
fitted.jvn_model(),
fitted.kk_model(),
jvn_nowcast(),
kk_nowcast(),
logLik.jvn_model(),
logLik.kk_model(),
nobs.jvn_model(),
nobs.kk_model(),
plot.jvn_model(),
plot.kk_model(),
predict.jvn_model(),
predict.kk_model(),
print.jvn_model(),
print.kk_model(),
residuals.jvn_model(),
residuals.kk_model(),
states(),
summary.jvn_model(),
summary.kk_model(),
vcov.kk_model()
Examples
# \donttest{
gdp_growth <- dplyr::filter(
tsbox::ts_pc(reviser::gdp),
id == "EA",
time >= min(pub_date),
time <= as.Date("2020-01-01")
)
gdp_growth <- tidyr::drop_na(gdp_growth)
df <- get_nth_release(gdp_growth, n = 0:3)
fit <- jvn_nowcast(df = df, e = 4, ar_order = 2, include_noise = FALSE)
vcov(fit)
#> rho_1 rho_2 sigma_e sigma_nu_1
#> rho_1 2.660036e-02 -1.863963e-02 3.239221e-04 -1.510816e-07
#> rho_2 -1.863963e-02 2.622187e-02 -3.341437e-04 6.838604e-08
#> sigma_e 3.239221e-04 -3.341437e-04 1.584550e-03 1.898457e-08
#> sigma_nu_1 -1.510816e-07 6.838604e-08 1.898457e-08 3.463884e-05
#> sigma_nu_2 -6.403616e-08 2.886113e-08 7.891829e-09 7.288616e-12
#> sigma_nu_3 -3.403149e-08 1.554012e-08 4.357512e-09 3.981991e-12
#> sigma_nu_4 -1.247296e-02 1.038048e-02 1.758290e-02 1.005225e-07
#> sigma_nu_2 sigma_nu_3 sigma_nu_4
#> rho_1 -6.403616e-08 -3.403149e-08 -1.247296e-02
#> rho_2 2.886113e-08 1.554012e-08 1.038048e-02
#> sigma_e 7.891829e-09 4.357512e-09 1.758290e-02
#> sigma_nu_1 7.288616e-12 3.981991e-12 1.005225e-07
#> sigma_nu_2 1.959230e-05 1.653046e-12 4.664557e-08
#> sigma_nu_3 1.653046e-12 1.278599e-05 2.038724e-08
#> sigma_nu_4 4.664557e-08 2.038724e-08 -3.784373e-01
# }