ggseas (version 0.3.0)

stat_seas: X13 seasonal adjustment Stat

Description

Conducts X13-SEATS-ARIMA seasonal adjustment on the fly for ggplot2

Usage

stat_seas(mapping = NULL, data = NULL, geom = "line",
  position = "identity", show.legend = NA, inherit.aes = TRUE, start,
  frequency, x13_params = NULL, index.ref = NULL, index.basis = 100, ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the t

data

The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot. A da

geom

The geometric object to use display the data

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

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.

start

The starting point for the time series, in a format suitable for ts()

frequency

The frequency for the time series

x13_params

a list of other parameters for seas

index.ref

if not NULL, a vector of integers indicating which elements of the beginning of each series to use as a reference point for converting to an index. If NULL, no conversion takes place and the data are presented on the original scale.

index.basis

if index.ref is not NULL, the basis point for converting to an index, most commonly 100 or 1000. See examples.

...

other arguments for the geom

See Also

seas Other time.series.stats.for.ggplot2: stat_decomp, stat_index, stat_rollapplyr, stat_stl

Examples

ap_df <- tsdf(AirPassengers)

# SEATS with defaults:
ggplot(ap_df, aes(x = x, y = y)) +
   stat_seas(start = c(1949, 1), frequency = 12)
   
# X11 with no outlier treatment:
ggplot(ap_df, aes(x = x, y = y)) +
  stat_seas(start = c(1949, 1), frequency = 12, x13_params = list(x11 = "", outlier = NULL))

# Multiple time series example:    
ggplot(ldeaths_df, aes(x = YearMon, y = deaths, colour = sex)) +
  geom_point() +
  facet_wrap(~sex) +
  stat_seas(start = c(1974, 1), frequency = 12) +
  ggtitle("Seasonally adjusted lung deaths")
  
# example use of index:  
ggplot(ap_df, aes(x = x, y = y)) +
  stat_seas(start = c(1949, 1), frequency = 12, x13_params = list(x11 = "", outlier = NULL),
  index.ref = 1, index.basis = 1000) +
  labs(y = "Seasonally adjusted index\n(first observation = 1000)")