sacf: Autocorrelation Plots for Multiple Seasonal Cycles

In msarima: Multi-Seasonal ARIMA Models

Autocorrelation Plots for Multiple Seasonal Cycles

Description

Sample autocorrelation (sacf) and partial autocorrelation (spacf) functions that highlight the lags belonging to one or more seasonal cycles, so that the seasonal structure of a multi-seasonal series is visible at a glance. ggsacf() and ggspacf() are the ggplot2 equivalents.

Usage

sacf(
  x,
  season = NULL,
  lag.max = NULL,
  ci = 0.95,
  col = NULL,
  main = NULL,
  ylab = "ACF",
  plot = TRUE,
  ...
)

spacf(x, ..., ylab = "PACF")

ggsacf(
  x,
  season = NULL,
  lag.max = NULL,
  ci = 0.95,
  main = NULL,
  ylab = "ACF",
  ...
)

ggspacf(x, ..., ylab = "PACF")

Arguments

x	A numeric vector, a ts/msts object, or a fitted msarima model (in which case the model residuals are used).
season	Numeric vector of seasonal periods to highlight, of any length. If NULL (default) the periods are taken from the msts/ts attributes of x, or from the fitted model.
lag.max	Maximum lag. Defaults to 3 * max(season), or to the stats::acf default when no seasonal period is available.
ci	Coverage of the confidence bands, as a probability. Default 0.95.
col	Colours used for the seasonal lags, one per element of season (recycled). Defaults to a colour-blind safe palette (Okabe and Ito, 2008), the same one used by ggsacf() and ggspacf().
main, ylab	Plot title and y-axis label.
plot	If TRUE (default) the correlogram is drawn.
...	Further arguments passed to stats::acf, and from spacf() and ggspacf() to sacf() and ggsacf().

Details

Lags that are multiples of more than one period (lag 168 with season = c(24, 168), say) are attributed to the longest matching period.

The series is treated as a plain numeric vector, so lags are always reported in number of observations and not in units of time. Leading and trailing NAs, such as those produced by differencing in msarima, are dropped (stats::na.contiguous).

Value

sacf() and spacf() invisibly return the stats::acf object, with the seasonal periods in the "season" attribute and, for each lag, the index of the period it belongs to in "season.group". ggsacf() and ggspacf() return a ggplot object.

References

Okabe, M. and Ito, K. (2008). Color Universal Design (CUD): How to make figures and presentations that are friendly to colorblind people. https://jfly.uni-koeln.de/color/

See Also

stats::acf, msarima

Examples

fit <- msarima(MAD_m40, order = c(1, 0, 2),
               seasonal = list(c(0, 1, 1), c(0, 1, 1)))

sacf(MAD_m40, lag.max = 200)   # periods 24 and 168 taken from the msts object
spacf(fit)                     # residual pacf, periods taken from the model

msarima documentation built on Nov. 12, 2026, 5:11 p.m.