forecast: Forecast future values

In itsmr: Time Series Analysis Using the Innovations Algorithm

Forecast future values

Description

Forecast future values

Usage

forecast(x, M, a, h = 10, opt = 2, alpha = 0.05)

Arguments

x	Time series data
M	Data model
a	ARMA model
h	Steps ahead
opt	Display option (0 silent, 1 tabulate, 2 plot and tabulate)
alpha	Level of significance

Details

The data model can be NULL for none. Otherwise M is a vector of function names and arguments.

Example:

M = c("log","season",12,"trend",1)

The above model takes the log of the data, then subtracts a seasonal component of period 12, then subtracts a linear trend component.

These are the available functions:

diff	Difference the data. Has a single argument, the lag.
hr	Subtract harmonic components. Has one or more arguments, each specifying the number of observations per harmonic.
log	Take the log of the data, has no arguments.
season	Subtract a seasonal component. Has a single argument, the number of observations per season.
trend	Subtract a trend component. Has a single argument, the order of the trend (1 linear, 2 quadratic, etc.)

At the end of the model there is an implicit subtraction of the mean operation. Hence the resulting time series always has zero mean.

All of the functions are inverted before the forecast results are displayed.

Value

Returns the following list invisibly.

pred	Predicted values
se	Standard errors (not returned for data models with log)
l	Lower bounds (95% confidence interval)
u	Upper bounds

See Also

arma Resid test

Examples

M = c("log","season",12,"trend",1)
e = Resid(wine,M)
a = arma(e,1,1)
forecast(wine,M,a)

itsmr documentation built on Aug. 6, 2022, 9:08 a.m.