dglnpdf

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function p = dglnpdf(n,alpha,beta)

%DGLNPDF Discrete generalized log-normal probability density function.
%
%   P = DGLNPDF(N,ALPHA,BETA) returns the probabilities for a discrete
%   version of the generalized log-normal probability density function. In
%   this case, Prob(x) ~ exp(-(log(x)/alpha)^beta) for x = 1:N.
%
%   See also DPLPDF, GENDEGDIST.
%
%   Reference:
%   * T. G. Kolda, A. Pinar, T. Plantenga and C. Seshadhri. A Scalable
%     Generative Graph Model with Community Structure,  arXiv:1302.6636,
%     March 2013. (http://arxiv.org/abs/1302.6636)
%
% Tamara G. Kolda, Ali Pinar, and others, FEASTPACK v1.1, Sandia National
% Laboratories, SAND2013-4136W, http://www.sandia.gov/~tgkolda/feastpack/,
% January 2014

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Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

p = exp(-((log((1:n)'))/alpha).^beta);
p = p / sum(p);

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