Learn R Programming

bsts (version 0.9.5)

plot.holiday: Plot Holiday Effects

Description

Plot the estimated effect of the given holiday.

Usage

PlotHoliday(holiday, model, show.raw.data = TRUE, ylim = NULL, …)

Arguments

holiday

An object of class Holiday.

model

A model fit by bsts containing either a RegressionHolidayStateModel or HierarchicalRegressionHolidayStateModel that includes holiday.

show.raw.data

Logical indicating if the raw data corresponding to holiday should be superimposed on the plot. The 'raw data' are the actual values of the target series, minus the value of the target series the day before the holiday began, which is a (somewhat poor) proxy for remaining state elements. The raw data can appear artificially noisy if there are other strong state effects such as a day-of-week effect for holidays that don't always occur on the same day of the week.

ylim

Limits on the vertical axis of the plots.

Extra arguments passed to boxplot.

Value

Returns invisible{NULL}.

See Also

bsts AddRandomWalkHoliday

Examples

Run this code
# NOT RUN {
  trend <- cumsum(rnorm(730, 0, .1))
  dates <- seq.Date(from = as.Date("2014-01-01"), length = length(trend),
    by = "day")
  y <- zoo(trend + rnorm(length(trend), 0, .2), dates)

  AddHolidayEffect <- function(y, dates, effect) {
    ## Adds a holiday effect to simulated data.
    ## Args:
    ##   y: A zoo time series, with Dates for indices.
    ##   dates: The dates of the holidays.
    ##   effect: A vector of holiday effects of odd length.  The central effect is
    ##     the main holiday, with a symmetric influence window on either side.
    ## Returns:
    ##   y, with the holiday effects added.
    time <- dates - (length(effect) - 1) / 2
    for (i in 1:length(effect)) {
      y[time] <- y[time] + effect[i]
      time <- time + 1
    }
    return(y)
  }

  ## Define some holidays.
  memorial.day <- NamedHoliday("MemorialDay")
  memorial.day.effect <- c(.3, 3, .5)
  memorial.day.dates <- as.Date(c("2014-05-26", "2015-05-25"))
  y <- AddHolidayEffect(y, memorial.day.dates, memorial.day.effect)
  
  presidents.day <- NamedHoliday("PresidentsDay")
  presidents.day.effect <- c(.5, 2, .25)
  presidents.day.dates <- as.Date(c("2014-02-17", "2015-02-16"))
  y <- AddHolidayEffect(y, presidents.day.dates, presidents.day.effect)
  
  labor.day <- NamedHoliday("LaborDay")
  labor.day.effect <- c(1, 2, 1)
  labor.day.dates <- as.Date(c("2014-09-01", "2015-09-07"))
  y <- AddHolidayEffect(y, labor.day.dates, labor.day.effect)
  
  ## The holidays can be in any order.
  holiday.list <- list(memorial.day, labor.day, presidents.day)
  number.of.holidays <- length(holiday.list)
  
  ## In a real example you'd want more than 100 MCMC iterations.
  niter <- 100
  ss <- AddLocalLevel(list(), y)
  ss <- AddRegressionHoliday(ss, y, holiday.list = holiday.list)
  model <- bsts(y, state.specification = ss, niter = niter)

  PlotHoliday(memorial.day, model)
# }

Run the code above in your browser using DataLab