| tslm {forecast} | R Documentation |
tslm is used to fit linear models to time series including trend and seasonality components.
tslm(formula, data, lambda=NULL, ...)
formula |
an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. |
data |
an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lm is called. |
lambda |
Box-Cox transformation parameter. Ignored if NULL. Otherwise, data are transformed via a Box-Cox transformation. |
... |
Other arguments passed to |
tslm is largely a wrapper for lm() except that it allows variables "trend" and "season" which are created on the fly from the time series characteristics of the data. The variable "trend" is a simple time trend and "season" is a factor indicating the season (e.g., the month or the quarter depending on the frequency of the data).
Returns an object of class "lm".
Rob J Hyndman
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))