plot.mforecast {forecast} | R Documentation |
Plots historical data with multivariate forecasts and prediction intervals.
autoplot
will produce an equivelant plot as a ggplot object.
## S3 method for class 'mforecast' plot(x, main=paste("Forecasts from",x$method),xlab="time",...) ## S3 method for class 'mforecast' autoplot(object, plot.conf=TRUE, gridlayout=NULL, ...)
x |
Multivariate forecast object of class |
object |
Multivariate forecast object of class |
main |
Main title. Default is the forecast method. For autoplot, specify a vector of titles for each plot. |
xlab |
X-axis label. For autoplot, specify a vector of labels for each plot. |
plot.conf |
If |
gridlayout |
A matrix of positions for the each forecast plot to be positioned. |
... |
additional arguments to each individual |
Mitchell O'Hara-Wild
Hyndman and Athanasopoulos (2014) Forecasting: principles and practice, OTexts: Melbourne, Australia. http://www.otexts.org/fpp/
library(ggplot2) lungDeaths <- cbind(mdeaths, fdeaths) fit <- tslm(lungDeaths ~ trend + season) fcast <- forecast(fit, h=10) plot(fcast) autoplot(fcast) carPower <- as.matrix(mtcars[,c("qsec","hp")]) carmpg <- mtcars[,"mpg"] fit <- lm(carPower ~ carmpg) fcast <- forecast(fit, newdata=data.frame(carmpg=30)) plot(fcast, xlab="Year") autoplot(fcast, xlab=rep("Year",2))