forecast.mlm
is used to predict multiple linear models, especially those involving trend and seasonality components.## S3 method for class 'mlm':
forecast(object, newdata, h = 10, level = c(80, 95),
fan = FALSE, lambda = object$lambda, biasadj = FALSE, ts = TRUE, ...)
h
forecasts are produced.TRUE
, level is set to seq(51,99,by=3). This is suitable for fan plots.newdata
present.NULL
. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.TRUE
, the forecasts will be treated as time series provided the original data is a time series; the newdata
will be interpreted as related to the subsequent time periods. If FALSE
, any time series attributes of thforecast.lm()
.mforecast
".The function summary
is used to obtain and print a summary of the
results, while the function plot
produces a plot of the forecasts and prediction intervals.
The generic accessor functions fitted.values
and residuals
extract useful features of the value returned by forecast.lm
.
An object of class "mforecast"
is a list containing at least the following elements:
forecast.mlm
is largely a wrapper for forecast.lm()
except that it allows forecasts to be generated on multiple series. Also, the output is reformatted into a mforecast
object.tslm
, forecast.lm
, lm
.lungDeaths <- cbind(mdeaths, fdeaths)
fit <- tslm(lungDeaths ~ trend + season)
fcast <- forecast(fit, h=10)
carPower <- as.matrix(mtcars[,c("qsec","hp")])
carmpg <- mtcars[,"mpg"]
fit <- lm(carPower ~ carmpg)
fcast <- forecast(fit, newdata=data.frame(carmpg=30))
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