📄 hyppdf.m
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function y=hyppdf(x,alpha,beta,delta,mu);
%HYPPDF Hyperbolic probability density function (pdf).
% Y=HYPPDF(X,ALPHA,BETA,DELTA,MU) returns the pdf of the hyperbolic
% distribution with shape parameter ALPHA, skewness parameter BETA,
% scale parameter DELTA and location parameter MU, evaluated at the
% values in X.
%
% Reference(s):
% [1] R.Weron (2004) "Computationally intensive Value at Risk
% calculations", in "Handbook of Computational Statistics: Concepts and
% Methods", eds. J.E. Gentle, W. Haerdle, Y. Mori, Springer, Berlin,
% 911-950.
% [2] R.Weron (2007) "Modeling and Forecasting Electricity Loads and
% Prices: A Statistical Approach", Wiley, Chichester.
% Written by Adam Misiorek and Rafal Weron (2006.09.22)
% Copyright (c) 2006 by Rafal Weron
% Set lambda of the generalized hyperbolic distribution to 1
lambda = 1;
if (delta>0)&(alpha>abs(beta))
kappa = (alpha^2-beta^2)^(lambda/2)/(sqrt(2*pi)*alpha^(lambda-1/2)*delta^lambda*besselk(lambda,delta*sqrt(alpha^2-beta^2)));
y = kappa*(delta^2+(x-mu).^2).^((lambda-1/2)/2).*besselk(lambda-1/2,alpha*sqrt(delta^2+(x-mu).^2)).*exp(beta*(x-mu));
else
y = Inf*ones(size(x));
end;
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