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    Metadata details:
    filename: priorGamma.m
    path of file: ./repos/Gaussian-Process-Regression/gpml-matlab-v4.2-2018-06-11/prior
    
    the code of the file until where you have to start completion: function [lp,dlp] = priorGamma(k,t,x)

% Univariate Gamma hyperparameter prior distribution.
% Compute log-likelihood and its derivative or draw a random sample.
% The prior distribution is parameterized as:
%
%   p(x) = exp(x/t)/gamma(k)*x^(k-1)/t^k
%
% where k(1x1) is the shape parameter, t(1x1) is the scale parameter
% and x(1xN) contains query hyperparameters for prior evaluation.
%
% Sampling is done using the algorithm from p. 53 of the paper Generating gamma
% variates by a modified rejection technique by J.H. Ahrens and U. Dieter, 1982,
% ACM, 25, 47â€“54.
%

    
function [lp,dlp] = priorGamma(k,t,x)

% Univariate Gamma hyperparameter prior distribution.
% Compute log-likelihood and its derivative or draw a random sample.
% The prior distribution is parameterized as:
%
%   p(x) = exp(x/t)/gamma(k)*x^(k-1)/t^k
%
% where k(1x1) is the shape parameter, t(1x1) is the scale parameter
% and x(1xN) contains query hyperparameters for prior evaluation.
%
% Sampling is done using the algorithm from p. 53 of the paper Generating gamma
% variates by a modified rejection technique by J.H. Ahrens and U. Dieter, 1982,
% ACM, 25, 47â€“54.
%
% For more help on design of priors, try "help priorDistributions".
%
% Copyright (c) by Roman Garnett and Hannes Nickisch, 2014-09-08.
%
% See also PRIORDISTRIBUTIONS.M.

if nargin<2, error('k and t parameters need to be provided'), end