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Confidence Intervals for Trend-Cycle Estimates

Source: R/confint.R
confint_tc.Rd

Computes confidence intervals for trend-cycle estimates of class "tc_estimates".

Usage

# S3 method for class 'henderson'
confint(object, parm, level = 0.95, asymmetric_var = TRUE, ...)

# S3 method for class 'clf'
confint(object, parm, level = 0.95, asymmetric_var = TRUE, ...)

# S3 method for class 'robust_henderson'
confint(object, parm, level = 0.95, asymmetric_var = TRUE, ...)

Arguments

object

An object of class "tc_estimates".

parm

Unused parameter, kept for compatibility with the generic function.

level

The confidence level required (defaults to 0.95).

asymmetric_var

Logical. If TRUE (the default), the variance is estimated for each asymmetric filter. If FALSE, the variance associated with the symmetric filter is used throughout.

...

Additional arguments (currently unused).

Value

A matrix or mts object with the filtered series and the lower and upper bounds of the confidence interval.

Details

See rjd3filters::confint_filter() for details on the computation of confidence intervals.

Examples

if (FALSE) { # rjd3jars::check_java_version(silent = TRUE)
x <- cars_registrations
tc <- henderson_smoothing(x)
confint <- confint(tc)

plot(confint, plot.type = "single",
   col = c("red", "black", "black"),
   lty = c(1, 2, 2), xlab = NULL, ylab = NULL)
lines(x, col = "grey")
legend("topleft", legend = c("x", "Smoothed", "CI (95%)"),
     col= c("grey", "red", "black"), lty = c(1, 1, 2))
}