# forecast.lm

From forecast v7.3
by Rob Hyndman

##### Forecast a linear model with possible time series components

`forecast.lm`

is used to predict linear models, especially those involving trend and seasonality components.

- Keywords
- stats

##### Usage

`"forecast"(object, newdata, h=10, level=c(80,95), fan=FALSE, lambda=object$lambda, biasadj=FALSE, ts=TRUE, ...)`

##### Arguments

- object
- Object of class "lm", usually the result of a call to
`lm`

or`tslm`

. - newdata
- An optional data frame in which to look for variables with which to predict. If omitted, it is assumed that the only variables are trend and season, and
`h`

forecasts are produced. - level
- Confidence level for prediction intervals.
- fan
- If
`TRUE`

, level is set to seq(51,99,by=3). This is suitable for fan plots. - h
- Number of periods for forecasting. Ignored if
`newdata`

present. - lambda
- Box-Cox transformation parameter. Ignored if
`NULL`

. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation. - biasadj
- Use adjusted back-transformed mean for Box-Cox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities.
- ts
- If
`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 the original data will be ignored. - ...
- Other arguments passed to
`predict.lm()`

.

##### Details

`forecast.lm`

is largely a wrapper for `predict.lm()`

except that it allows variables "trend" and "season" which are created on the fly from the time series characteristics of the data. Also, the output is reformatted into a `forecast`

object.

##### Value

`forecast`

".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 `"forecast"`

is a list containing at least the following elements:
is a list containing at least the following elements:##### See Also

##### Examples

```
y <- ts(rnorm(120,0,3) + 1:120 + 20*sin(2*pi*(1:120)/12), frequency=12)
fit <- tslm(y ~ trend + season)
plot(forecast(fit, h=20))
```

*Documentation reproduced from package forecast, version 7.3, License: GPL (>= 2)*

### Community examples

Looks like there are no examples yet.