R: Multivariate forecast plot

autoplot.mforecast {forecast} | R Documentation

## Multivariate forecast plot

### Description

Plots historical data with multivariate forecasts and prediction intervals.

### Usage

    ## S3 method for class 'mforecast'
    autoplot(object, PI = TRUE, facets = TRUE,
      colour = FALSE, ...)

    ## S3 method for class 'mforecast'
    autolayer(object, series = NULL, PI = TRUE, ...)

    ## S3 method for class 'mforecast'
    plot(x, main = paste("Forecasts from", unique(x$method)),
      xlab = "time", ...)

### Arguments

`object` | Multivariate forecast object of class `mforecast`. Used for ggplot graphics (S3 method consistency).
`PI` | If `FALSE`, confidence intervals will not be plotted, giving only the forecast line.
`facets` | If TRUE, multiple time series will be faceted. If FALSE, each series will be assigned a colour.
`colour` | If TRUE, the time series will be assigned a colour aesthetic
`...` | additional arguments to each individual `plot`.
`series` | Matches an unidentified forecast layer with a coloured object on the plot.
`x` | Multivariate forecast object of class `mforecast`.
`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.

### Details

`autoplot` will produce an equivalent plot as a ggplot object.

### Author(s)

Mitchell O'Hara-Wild

### References

Hyndman and Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. https://OTexts.org/fpp2/

### See Also

`plot.forecast`, `plot.ts`

### Examples

    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))

[Package forecast version 8.4 Index]