FracDiff: Fast Fractional Differencing

View source: R/FCVAR_aux.R

FracDiffR Documentation

Fast Fractional Differencing


FracDiff is a fractional differencing procedure based on the fast fractional difference algorithm of Jensen & Nielsen (2014).


FracDiff(x, d)



A matrix of variables to be included in the system.


The order of fractional differencing.


A vector or matrix dx equal to (1-L)^d x of the same dimensions as x.


This function differs from the diffseries function in the fracdiff package, in that the diffseries function demeans the series first. In particular, the difference between the out put of the function calls FCVAR::FracDiff(x - mean(x), d = 0.5) and fracdiff::diffseries(x, d = 0.5) is numerically small.


Jensen, A. N. and M. Ø. Nielsen (2014). "A fast fractional difference algorithm," Journal of Time Series Analysis 35, 428-436.

See Also

FCVARoptions to set default estimation options. FCVARestn calls GetParams, which calls TransformData to estimate the FCVAR model. TransformData in turn calls FracDiff and Lbk to perform the transformation.

Other FCVAR auxiliary functions: FCVARforecast(), FCVARlikeGrid(), FCVARsimBS(), FCVARsim(), plot.FCVAR_grid()


WN <- matrix(stats::rnorm(200), nrow = 100, ncol = 2)
MVWNtest_stats <- MVWNtest(x = WN, maxlag = 10, printResults = 1)
x <- FracDiff(x = WN, d = - 0.5)
MVWNtest_stats <- MVWNtest(x = x, maxlag = 10, printResults = 1)
WN_x_d <- FracDiff(x, d = 0.5)
MVWNtest_stats <- MVWNtest(x = WN_x_d, maxlag = 10, printResults = 1)

FCVAR documentation built on May 5, 2022, 9:06 a.m.