%              acf : computes the autocorrelation function of the columns of series up to lag ilag
%         acfilter : computes the autocorrelation function of the columns of series up to lag ilag
%              acv : computes the autocorrelation function of the arfima model
%         arfima_d : A demonstrated example using ARFIMA                                                    
%          docovar : estimates the Variance-covariance matrix of the arfima model
%     doestimation : estimates coefficients, with estimated residual variance for EML and MPL, using BFGS
%       doforecast : The forecasting function in the arfima model
%           doinit : The initialization of the parameters for arfima model
%      estimategph : The log-periodogram regression method for estimating d.
%           flipma : A function to ensure that the roots of the MA part are stationary ,
%          hessian : Computes finite difference Hessian
%          hypergm : The hypergeometric function
%     isstationary : check if the roots of the AR part and d are stationary ones or not 
%        lagmatrix X Create a lagged time series matrix.
%         logemlik : The exact maximum likelihood function for arfima
%         logmplik : The modified profile likelihood function for arfima
%             olsv : least-squares regression 
%             pacf : Return a matrix with the residuals from the filter based on the ACF applied to the columns 
%        powerdiff : This operation involves computing a long (in theory infinite, in practice long, but truncated)
%          solvear : Solve the Yule-Walker equations for AR values
%          solvema : Solve for MA values using the Tunnicliffe-Wilson method
%       trimmatrix : Truncating the matrix to nT rows
