PCT: Percentage Change Transformation

In RebeccaSalles/TSPred: Functions for Benchmarking Time Series Prediction

Description

The pct() function returns a transformation of the provided time series using a Percentage Change transformation. pct.rev() reverses the transformation.

Usage

pct(x)

pct.rev(p, xi, addinit = TRUE)

Arguments

x	A numeric vector or univariate time series of class ts.
p	A numeric vector or univariate time series of percentage changes. Possibly returned by pct().
xi	Initial value/observation of x (x[1]). First known non-transformed value used to recursively obtain the original series.
addinit	If TRUE, xi is included in the return.

Details

The Percentage Change transformation is given approximately by

log(x[2:n] / x[1:(n-1)] ) = log( x[2:n] ) - log( x[1:(n-1)] )

where n=length(x).

Value

A vector of length length(x)-1 containing the transformed values.

Author(s)

Rebecca Pontes Salles

References

R.H. Shumway and D.S. Stoffer, 2010, Time Series Analysis and Its Applications: With R Examples. 3rd ed. 2011 edition ed. New York, Springer.

See Also

Other transformation methods: Diff(), LogT(), WaveletT(), emd(), mas(), mlm_io(), outliers_bp(), train_test_subset()

Examples

data(NN5.A)
ts <- na.omit(NN5.A[,10])
length(ts)

p <- pct(ts)
length(p)

p_rev <- pct.rev(p, attributes(p)$xi)

all(round(p_rev,4)==round(ts,4))

RebeccaSalles/TSPred documentation built on April 6, 2021, 2:44 a.m.