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Added unit test for priordens routine.

time-shift
Stéphane Adjemian (Charybdis) 2015-12-15 09:14:50 +01:00
parent adb5a2359d
commit 74283c45d2
1 changed files with 85 additions and 2 deletions
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87
matlab/priordens.m
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@ -1,4 +1,4 @@
function [logged_prior_density, dlprior, d2lprior, info] = priordens(x, pshape, p6, p7, p3, p4,initialization)
function [logged_prior_density, dlprior, d2lprior, info] = priordens(x, pshape, p6, p7, p3, p4, initialization) % --*-- Unitary tests --*--
% Computes a prior density for the structural parameters of DSGE models
%
% INPUTS
@ -189,4 +189,87 @@ end
if nargout==3,
d2lprior = diag(d2lprior);
end
end
%@test:1
%$ % Fill global structures with required fields...
%$ prior_trunc = 1e-10;
%$ p0 = repmat([1; 2; 3; 4; 5; 6; 8], 2, 1); % Prior shape
%$ p1 = .4*ones(14,1); % Prior mean
%$ p2 = .2*ones(14,1); % Prior std.
%$ p3 = NaN(14,1);
%$ p4 = NaN(14,1);
%$ p5 = NaN(14,1);
%$ p6 = NaN(14,1);
%$ p7 = NaN(14,1);
%$
%$ for i=1:14
%$ switch p0(i)
%$ case 1
%$ % Beta distribution
%$ p3(i) = 0;
%$ p4(i) = 1;
%$ [p6(i), p7(i)] = beta_specification(p1(i), p2(i)^2, p3(i), p4(i));
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 1);
%$ case 2
%$ % Gamma distribution
%$ p3(i) = 0;
%$ p4(i) = Inf;
%$ [p6(i), p7(i)] = gamma_specification(p1(i), p2(i)^2, p3(i), p4(i));
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 2);
%$ case 3
%$ % Normal distribution
%$ p3(i) = -Inf;
%$ p4(i) = Inf;
%$ p6(i) = p1(i);
%$ p7(i) = p2(i);
%$ p5(i) = p1(i);
%$ case 4
%$ % Inverse Gamma (type I) distribution
%$ p3(i) = 0;
%$ p4(i) = Inf;
%$ [p6(i), p7(i)] = inverse_gamma_specification(p1(i), p2(i)^2, p3(i), 1, false);
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 4);
%$ case 5
%$ % Uniform distribution
%$ [p1(i), p2(i), p6(i), p7(i)] = uniform_specification(p1(i), p2(i), p3(i), p4(i));
%$ p3(i) = p6(i);
%$ p4(i) = p7(i);
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 5);
%$ case 6
%$ % Inverse Gamma (type II) distribution
%$ p3(i) = 0;
%$ p4(i) = Inf;
%$ [p6(i), p7(i)] = inverse_gamma_specification(p1(i), p2(i)^2, p3(i), 2, false);
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 6);
%$ case 8
%$ % Weibull distribution
%$ p3(i) = 0;
%$ p4(i) = Inf;
%$ [p6(i), p7(i)] = weibull_specification(p1(i), p2(i)^2, p3(i));
%$ p5(i) = compute_prior_mode([p6(i) p7(i)], 8);
%$ otherwise
%$ error('This density is not implemented!')
%$ end
%$ end
%$
%$ % Call the tested routine
%$ try
%$ % Initialization of priordens.
%$ lpdstar = priordens(p5, p0, p6, p7, p3, p4, true);
%$ % Do simulations in a loop and estimate recursively the mean and teh variance.
%$ LPD = NaN(10000,1);
%$ for i = 1:10000
%$ draw = p5+randn(size(p5))*.02;
%$ LPD(i) = priordens(p5, p0, p6, p7, p3, p4);
%$ end
%$ t(1) = true;
%$ catch
%$ t(1) = false;
%$ end
%$
%$ if t(1)
%$ t(2) = all(LPD<=lpdstar);
%$ end
%$ T = all(t);
%@eof:1