private static ArtaProcessNormal CreateArtaProcessN(NormalDistribution normal, double[] artaCorrelationCoefficients, RandomGenerator random)// throws NotStationaryException
{
ArtaProcessNormal arta = null;
// By definition: arCorrelationCoefficients == artaCorrelationCoefficients
ArProcess ar = ArProcessFactory.CreateArProcess(artaCorrelationCoefficients, random);
arta = new ArtaProcessNormal(ar, normal.getNumericalMean(), normal.getNumericalVariance());
return(arta);
}
private static ArtaProcessGeneral CreateArtaProcessG(RealDistribution distribution, double[] artaCorrelationCoefficients, RandomGenerator random) //throws NotStationaryException
{
ArtaProcessGeneral arta = null;
AutocorrelationFitter fitter = new AutocorrelationFitter(distribution);
double[] arCorrelationCoefficients = fitter.FitArAutocorrelations(artaCorrelationCoefficients, DEFAULT_ERROR);
ArProcess ar = ArProcessFactory.CreateArProcess(arCorrelationCoefficients, random);
arta = new ArtaProcessGeneral(ar, distribution);
return(arta);
}
private static ArtaProcessUniform createArtaProcessU(UniformRealDistribution uniform, double[] artaCorrelationCoefficients, RandomGenerator random) //throws NotStationaryException
{
ArtaProcessUniform arta = null;
int dim = artaCorrelationCoefficients.Length;
double[] arCorrelationCoefficients = new double[dim];
for (int i = 0; i < dim; i++)
{
arCorrelationCoefficients[i] = 2 * Math.Sin(Math.PI * artaCorrelationCoefficients[i] / 6);
}
ArProcess ar = ArProcessFactory.CreateArProcess(arCorrelationCoefficients, random);
arta = new ArtaProcessUniform(ar, uniform.getSupportLowerBound(), uniform.getSupportUpperBound());
return(arta);
}
