AutoArimaTSPred: Method to predict according to an ARIMA model.

In elisa-esteban/TSPred: Point and std prediction of time series

Description

This method implements the predicted value and their standard deviation according to an ARIMA model.

Usage

AutoArimaTSPred(x, VarNames, frequency = 12L, forward = 2L)

## S4 method for signature 'vector'
AutoArimaTSPred(x, VarNames, frequency = 12L,
  forward = 2L)

## S4 method for signature 'StQList'
AutoArimaTSPred(x, VarNames, frequency = 12L,
  forward = 2L)

Arguments

x	object upon which the prediction will be made.
VarNames	character vector with the variable names for which the prediction will be made; by default it is NULL.
frequency	integer indicating the frequency of time series; by default it is 12L.
forward	integer indicating the number of periods ahead when the prediction will be made; by default it is 2L.

Value

It returns a data.table with components Pred and STD, containing the point prediction and the estimated standard deviations, respectively, for each variable.

Examples

# Predicting one and two months ahead in time
data(Example1.TS)
AutoArimaTSPred(Example1.TS, forward = 1L)
AutoArimaTSPred(Example1.TS, forward = 2L)

# Predicting upon a times series with many NA values
data(Example2.TS)
AutoArimaTSPred(Example2.TS, forward = 1L)

## Not run: 
# With an object of class StQList
data(StQListExample)
VarNames <- c('ActivEcono_35._6._2.1.4._0', 'GeoLoc_35._6._2.1._1.2.5.')
AutoArimaTSPred(StQListExample, VarNames)

## End(Not run)

elisa-esteban/TSPred documentation built on April 28, 2020, 3:58 a.m.