ggseas (version 0.2.0)

stat_decomp: Classical seasonal adjustment Stat

Description

Conducts seasonal adjustment on the fly for ggplot2, from classical seasonal decomposition by moving averages

Usage

stat_decomp(mapping = NULL, data = NULL, geom = "line",
  position = "identity", show.legend = NA, inherit.aes = TRUE, frequency,
  type = c("additive", "multiplicative"), ...)

Arguments

mapping

The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.

data

A layer specific dataset - only needed if you want to override the plot defaults.

geom

The geometric object to use display the data

position

The position adjustment to use for overlapping points on this layer

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g.

frequency

The frequency for the time series

type

The type of seasonal component

...

other arguments for the geom

Details

Classical decomposition is a very basic way of performing seasonal adjustment and is not recommended if you have access to X13-SEATS-ARIMA (stat_seas). stat_decomp cannot allow the seasonality to vary over time, or take outliers into account in calculating seasonality.

See Also

decompose Other time.series.stats.for.ggplot2: stat_seas, stat_stl

Examples

ap_df <- tsdf(AirPassengers)

# default additive decomposition (doesn't work well in this case!):
ggplot(ap_df, aes(x = x, y = y)) +
   stat_decomp(frequency = 12)

# multiplicative decomposition, more appropriate:
ggplot(ap_df, aes(x = x, y = y)) +
   stat_decomp(frequency = 12, type = "multiplicative")

ggplot(ldeaths_df, aes(x = YearMon, y = deaths, colour = sex)) +
  geom_point() +
  facet_wrap(~sex) +
  stat_decomp(frequency = 12) +
  ggtitle("Seasonally adjusted lung deaths")