FracDiff: Fast Fractional Differencing

In FCVAR: Estimation and Inference for the Fractionally Cointegrated VAR

Fast Fractional Differencing

Description

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

Usage

FracDiff(x, d)

Arguments

x	A matrix of variables to be included in the system.
d	The order of fractional differencing.

Value

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

Note

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.

References

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()

Examples

set.seed(42)
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.