FracDiff | R Documentation |

`FracDiff`

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

FracDiff(x, d)

`x` |
A matrix of variables to be included in the system. |

`d` |
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.

`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()`

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.

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