inst/unitTests/runit.sged.R

In fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling

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# Copyrights (C)
# for this R-port: 
#   1999 - 2008, Diethelm Wuertz, Rmetrics Foundation, GPL
#   Diethelm Wuertz <wuertz@itp.phys.ethz.ch>
#   info@rmetrics.org
#   www.rmetrics.org
# for the code accessed (or partly included) from other R-ports:
#   see R's copyright and license files
# for the code accessed (or partly included) from contributed R-ports
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#   see Rmetrics's copyright file


################################################################################ 
# FUNCTION:              GED DISTRIBUTION:
#  dged                   Density for the Generalized Error Distribution
#  pged                   Probability function for the GED
#  qged                   Quantile function for the GED
#  rged                   Random Number Generator for the GED
# FUNCTION:              SKEW GED DISTRIBUTION:
#  dsged                  Density for the skewed GED
#  psged                  Probability function for the skewed GED
#  qsged                  Quantile function for the skewed GED
#  rsged                  Random Number Generator for the skewed GED
# FUNCTION:              GED DISTRIBUTION SLIDER:
#  sgedSlider            Displays Generalized Error Distribution and RVS
# FUNCTION:              PARAMETER ESTIMATION:
#  gedFit                 Fit the parameters for a GED distribution
#  sgedFit                Fit the parameters for a skew GED distribution
# FUNCTION:              MOMENTS:
################################################################################


test.sgedDis <- 
    function()
{       
    # Generalized Error Distribution:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(4711, kind = "Marsaglia-Multicarry")
    
    # Test:
    test = fBasics::distCheck("ged",  mean = 0, sd = 1, nu = 2, robust = FALSE) 
    print(test)                                     
       
    # Skew Generalized Error Distribution:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(1953, kind = "Marsaglia-Multicarry")
    test = fBasics::distCheck("sged", mean = 0, sd = 1, nu = 2, xi = 0.8, robust = FALSE) 
    print(test)                                       

    ## 2022-07-27 GB check fixes related to issue #6061, see NEWS and the source code
    stopifnot( all( diff(qsged(c(0.49, 0.5, 0.51))) > 0) )
    stopifnot( all( diff(psged(qsged(c(0.49, 0.5, 0.51)))) > 0) )
    
    # Return Value:
    return()    
}


# ------------------------------------------------------------------------------


test.sgedFit <- 
    function()
{      
    # Parameter Estimation:
    #  gedFit - Fit the parameters for a GED distribution
    
    # Generalized Error Distribution:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(4711, kind = "Marsaglia-Multicarry")
    
    # Series:
    x = rged(1000, mean = 0, nu = 2)
    
    # Fit:
    fit = gedFit(x)
    print(fit)
      
    # Fit the parameters for a skew GED distribution
    #  sgedFit - Fit the parameters for a skew GED distribution
    
    # Skew Generalized Error Distribution:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(4711, kind = "Marsaglia-Multicarry")
    x = rsged(1000, mean = 0, sd = 1, nu = 2, xi = 1.5)
    fit = sgedFit(x)
    print(fit)
    
    # Return Value:
    return()    
}


# ------------------------------------------------------------------------------


test.sgedSlider <- 
    function()
{   
    # Try Distribution:
    # sgedSlider(type = "dist")
    NA 
    
    # Try Random Variates:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(4711, kind = "Marsaglia-Multicarry")
    
    # sgedSlider(type = "rand")
    NA
    
    # Return Value:
    return()    
}


################################################################################