optimal_arfima_d.py

def optimal_d(DF, alpha=0.035, minimum = 0, maximum = 1):
    # Copy the dataframe
    df = DF.copy()
    # Estimate the best d based on the basic d range
    out = d_estimates_db(df,minimum,maximum)
    out.to_excel('out1.xlsx')
    # A try-except block to handle erros while getting a d with better decimals
    try:
        # Get the d value which critical value is closest to and higher than alpha
        d1 = out[out['pVal']>alpha].index.values[-1]
        # Get the d value which critical value is closest to and lower than alpha
        d2 = out[out['pVal']<alpha].index.values[0]
        # Estimate the best d between d1 and d2
        out = d_estimates_db(df,d1,d2)
        out.to_excel('out2.xlsx')
        try:
            # Get the d value which critical value is closest to and higher than alpha
            d1 = out[out['pVal']>alpha].index.values[-1]
            # Get the d value which critical value is closest to and lower than alpha
            d2 = out[out['pVal']<alpha].index.values[0]
            # Estimate the best d between d1 and d2
            out = d_estimates_db(df,d1,d2)
            out.to_excel('out3.xlsx')
            try:
                # Get the d value which critical value is closest to and higher than alpha
                d1 = out[out['pVal']>alpha].index.values[-1]
                # Get the d value which critical value is closest to and lower than alpha
                d2 = out[out['pVal']<alpha].index.values[0]
                # Set d as the average between d1 and d2 with four decimals
                d = round((d1+d2)/2,4)    
            except:
                # In case the try fails, assign d with the critical value which is closest to and higher than alpha
                d = out[out['pVal']<alpha].index.values[0]
        except:
            # In case the try fails, assign d with the critical value which is closest to and higher than alpha
            d = out[out['pVal']<alpha].index.values[0]
    except:
        # In case the try fails, assign d with the critical value which is closest to and higher than alpha
        d = out[out['pVal']<alpha].index.values[0]
    # Return the d value
    return d