mse: Accuracy/smoothness/timeliness criteria through spectral...

In palatej/rjdfilters: Trend-Cycle Extraction with Linear Filters

Accuracy/smoothness/timeliness criteria through spectral decomposition

Description

Accuracy/smoothness/timeliness criteria through spectral decomposition

Usage

mse(sweights, aweights, density = c("uniform", "rw"), passband = pi/6)

Arguments

sweights	moving_average object or weights of the symmetric filter (from 0 to n or -n to n).
aweights	moving_average object or weights of the asymmetric filter (from -n to m).
density	hypothesis on the spectral density: "uniform" (= white woise, the default) or "rw" (= random walk).
passband	passband threshold.

Value

The criteria

References

Wildi, Marc and McElroy, Tucker (2019). “The trilemma between accuracy, timeliness and smoothness in real-time signal extraction”. In: International Journal of Forecasting 35.3, pp. 1072–1084.

Examples

filter <- lp_filter(horizon = 6, kernel = "Henderson", endpoints = "LC")
sweights <- filter[,"q=6"]
aweights <- filter[,"q=0"]
mse(sweights, aweights)

palatej/rjdfilters documentation built on May 8, 2023, 6:28 a.m.