pct: Percentage Change Transformation
In TSPred: Functions for Benchmarking Time Series Prediction

Description Usage Arguments Details Value Author(s) References See Also Examples

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

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pct(x)

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

`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.

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).

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

Rebecca Pontes Salles

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.

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

1 2 3 4 5 6 7 8 9 10	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))