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Add unit tests for compute_prior_mode.m 

(cherry picked from commit 7d9c3ee365aba25c131b423596a1446eafd9c6ec)
time-shift
Johannes Pfeifer 2015-07-27 10:14:53 +02:00 committed by Stéphane Adjemian (Charybdis)
parent 09b4928ca8
commit 8c9736f93f
1 changed files with 73 additions and 2 deletions
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75
matlab/distributions/compute_prior_mode.m
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@ -1,4 +1,4 @@
function m = compute_prior_mode(hyperparameters,shape)
function m = compute_prior_mode(hyperparameters,shape) % --*-- Unitary tests --*--
% This function computes the mode of the prior distribution given the (two, three or four) hyperparameters
% of the prior distribution.
%
@ -96,4 +96,75 @@ switch shape
end
otherwise
error('Unknown prior shape!')
end
end
%@test:1
%$
%$ % Beta
%$ m1 = compute_prior_mode([2 1],1);
%$ m2 = compute_prior_mode([2 5 1 4],1); % Wolfram Alpha: BetaDistribution[2,5]
%$ % Check the results
%$ t(1) = dassert(m1,0,1e-6);
%$ t(2) = dassert(m2,1/5*3+1,1e-6);
%$ T = all(t);
%@eof:1
%$
%@test:2
%$ % Gamma
%$ m1 = compute_prior_mode([1 2],2);
%$ m2 = compute_prior_mode([9 0.5 1],2); % Wolfram Alpha: GammaDistribution[9,0.5]
%$ % Check the results
%$ t(1) = dassert(m1,0,1e-6);
%$ t(2) = dassert(m2,4+1,1e-6);
%$ T = all(t);
%@eof:2
%$
%@test:3
%$ % Normal
%$ m1 = compute_prior_mode([1 1],3);
%$ m2 = compute_prior_mode([2 5],3);
%$ % Check the results
%$ t(1) = dassert(m1,1,1e-6);
%$ t(2) = dassert(m2,2,1e-6);
%$ T = all(t);
%@eof:3
%$
%@test:4
%$ % Inverse Gamma I
%$ m1 = compute_prior_mode([8 2],4);
%$ m2 = compute_prior_mode([8 2 1],4);
%$ % Check the results
%$ t(1) = dassert(m1,1.632993161855452,1e-6);
%$ t(2) = dassert(m2,1.632993161855452+1,1e-6);
%$ T = all(t);
%@eof:4
%$
%@test:5
%$ % Uniform
%$ m1 = compute_prior_mode([0.5 1/sqrt(12)],5);
%$ m2 = compute_prior_mode([2 5 1 2],5);
%$ % Check the results
%$ t(1) = dassert(m1,0.5,1e-6);
%$ t(2) = dassert(m2,2,1e-6);
%$ T = all(t);
%@eof:5
%$
%@test:6
%$ % Inverse Gamma II, parameterized with s and nu where s=2*beta and nu=2*alpha
%$ m1 = compute_prior_mode([8 2],6); % Wolfram Alpha, parameterized with alpha beta: InversegammaDistribution[1,4]
%$ m2 = compute_prior_mode([8 4 1],6); % Wolfram Alpha, parameterized with alpha beta: InversegammaDistribution[2,4]
%$ % Check the results
%$ t(1) = dassert(m1,2,1e-6);
%$ t(2) = dassert(m2,1+4/3,1e-6);
%$ T = all(t);
%@eof:6
%$
%@test:7
%$ % Weibull
%$ m1 = compute_prior_mode([1 1],8);
%$ m2 = compute_prior_mode([1 2 1],8); % Wolfram Alpha: WeibullDistribution[2,1]
%$ % Check the results
%$ t(1) = dassert(m1,0,1e-6);
%$ t(2) = dassert(m2,1+1/sqrt(2),1e-6);
%$ T = all(t);
%@eof:7