auto_hpfj {jumps} | R Documentation |
Automatic selection of the optimal HP filter with jumps
Description
The regularization constant for the HP filter with jumps is the
maximal sum of standard deviations for the level disturbance. This value
has to be passed to the hpfj
function. The auto_hpfj
runs
hpfj
on a grid of regularization constants and returns the output
of hpfj
selected by the chosen information criterion.
Usage
auto_hpfj(
y,
grid = seq(0, sd(y, na.rm = TRUE) * 10, sd(y, na.rm = TRUE)/10),
ic = c("bic", "hq", "aic", "aicc"),
edf = TRUE
)
Arguments
y |
numeric vector cotaining the time series; |
grid |
numeric vector containing the grid for the argument |
ic |
string with information criterion for the choice: the default is "bic" (simulations show this is the best choice), but also "hq", "aic" and "aicc" are available; |
edf |
logical scalar: TRUE (default) if the number of degrees of freedom should be computed as "effective degrees of freedom" (Efron, 1986) as opposed to a more traditional way (although not supported by theory) when FALSE. |
Value
The same ouput as the hpjf
function corresponding to the best
choice according to the selected information criterion.
Examples
mod <- auto_hpfj(Nile)
plot(as.numeric(Nile))
lines(mod$smoothed_level)