ARFIMAFC: RATS modules to forecast fractionally differenced timeseries

these procedures generate multi-period-ahead dynamic forecasts of timeseries with a fractionally differenced representation (ARFIMA). fdfc.src forecasts an ARFIMA(0,d,0) series for specified d. fdarfc.src forecasts an ARFIMA(p,d,0) series for specified p and d: that is, a series with an AR(p) fractional representation. fdma1fc.src forecasts an ARFIMA(0,d,1) series for specified d.fractional differencing, ARMA, ARFIMA

GPHROB: RATS modules to perform tests for fractional integration of timeseries

These procedures, written for RATS version 4.2/4.3, calculate the GPH (Geweke & Porter-Hudak, 1983 J. Time Series Analysis) spectral regression estimator, the Robinson Gaussian semiparametric estimator (1995 Annals of Statistics) and the Robinson average periodogram long memory estimator (1994 Annals of Statistics) for fractional order of integration of a timeseries. Procedure GPH.SRC performs the test for a single series, for a given power value, and prints the result. Procedure GPHFN.SRC performs the test on differenced data and returns its results. This is useful if you are calculating GPH tests for a range of series and power values; you may then tabulate the results in a matrix. Procedure RGSER.SRC, originally written by Rob Schoen, has been corrected from the version posted on Estima's website. It implements Robinson's Gaussian semiparametric estimator. Program RAVPER.SRC, written by John Barkoulas, implements Robinson's average periodogram long memory estimator.