plot.iNZightTS: Draw a simple time series plot

In iNZightTS: Time Series for 'iNZight'

Description

Draws a plot of a given iNZightTS object with the trend superimposed.

Usage

## S3 method for class 'iNZightTS'
plot(
  x,
  multiplicative = FALSE,
  ylab = obj$currVar,
  xlab = "Date",
  title = "%var",
  animate = FALSE,
  t = 10,
  smoother = TRUE,
  aspect = 3,
  plot = TRUE,
  col = ifelse(forecast > 0, "#0e8c07", "red"),
  xlim = c(NA, NA),
  model.lim = NULL,
  seasonal.trend = FALSE,
  forecast = 0,
  ...
)

Arguments

x	an iNZightTS object
multiplicative	logical. If TRUE, a multiplicative model is used, otherwise an additive model is used by default.
ylab	a title for the y axis
xlab	a title for the x axis
title	a title for the graph
animate	logical, if true the graph is animated
t	smoothing parameter
smoother	logical, if TRUE the smoother will be drawn
aspect	the aspect ratio of the plot; it will be about ASPECT times wider than it is high
plot	logical, if FALSE, the graph isn't drawn
col	the colour of the smoothed trend line
xlim	axis limits, specified as dates
model.lim	limits of the series to use for modelling/forecast
seasonal.trend	logical, if TRUE seasonal+trend curve added
forecast	numeric, how many observations ahead to forecast (default is 0, no forecast)
...	additional arguments (not used)

Details

If animate is set to TRUE, a scatterplot of all points in the time series will appear followed by slowly drawn lines connecting the points, simulating the drawing of a time series by hand.

Value

a time series plot (constructed with ggplot2) is returned invisibly, which can be added to if desired.

Forecast

The predictions and prediction intervals are the result of models fitted by the Holt-Winters method. The amount of predicted observations is specified by the value of 'forecast'.

References

C.C Holt (1957) Forecasting seasonals and trends by exponentially weighted moving averages, ONR Research Memorandum, Carnegie Institute 52.

P.R Winters (1960) Forecasting sales by exponentially weighted moving averages, Management Science 6, 324–342.

Examples

t <- iNZightTS(visitorsQ)
plot(t)

# Forecast plot (8 quarterly forecasts):
plot(t, forecast = 8)

iNZightTS documentation built on Feb. 1, 2022, 1:08 a.m.