differencing.fast: Automatic differencing

In palatej/rjd3modelling: Time Series Modelling Functions with 'JDemetra+ 3.0'

Automatic differencing

Description

The series is differentiated till its variance is decreasing.

Usage

differencing.fast(data, period, mad = TRUE, centile = 90, k = 1.2)

Arguments

data	Series being differenced.
period	Period considered in the automatic differencing.
mad	Use of MAD in the computation of the variance (true by default).
centile	Percentage of the data used for computing the variance (90 by default).
k	tolerance in the decrease of the variance. The algorithm stops if the new varance is higher than k*the old variance.

Value

Stationary transformation

• ddata: data after differencing

• mean: mean correction

• differences:

  • lag: ddata(t)=data(t)-data(t-lag)

  • order: order of the differencing

Examples

z<-rjd3modelling::differencing.fast(log(rjd3toolkit::ABS$X0.2.09.10.M),12)

palatej/rjd3modelling documentation built on Jan. 3, 2023, 10:19 p.m.