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Merge pull request #1036 from JohannesPfeifer/cosmetics 

Speedup and compatibility
time-shift
Stéphane Adjemian 2015-08-27 11:46:16 +02:00
parent d125c2effc 26437e1c32
commit 9179d331e0
3 changed files with 32 additions and 33 deletions
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24
matlab/GetPosteriorParametersStatistics.m
View File

@ -377,18 +377,18 @@ fclose(fid);
function oo = Filloo(oo,name,type,postmean,hpdinterval,postmedian,postvar,postdecile,density)
eval(['oo.posterior_mean.' type '.' name ' = postmean;']);
eval(['oo.posterior_hpdinf.' type '.' name ' = hpdinterval(1);']);
eval(['oo.posterior_hpdsup.' type '.' name ' = hpdinterval(2);']);
eval(['oo.posterior_median.' type '.' name ' = postmedian;']);
eval(['oo.posterior_variance.' type '.' name ' = postvar;']);
eval(['oo.posterior_std.' type '.' name ' = sqrt(postvar);']);
eval(['oo.posterior_deciles.' type '.' name ' = postdecile;']);
eval(['oo.posterior_density.' type '.' name ' = density;']);
oo.posterior_mean.(type).(name) = postmean;
oo.posterior_hpdinf.(type).(name) = hpdinterval(1);
oo.posterior_hpdsup.(type).(name) = hpdinterval(2);
oo.posterior_median.(type).(name) = postmedian;
oo.posterior_variance.(type).(name) = postvar;
oo.posterior_std.(type).(name) = sqrt(postvar);
oo.posterior_deciles.(type).(name) = postdecile;
oo.posterior_density.(type).(name) = density;
function [post_mean,hpd_interval,post_var] = Extractoo(oo,name,type)
hpd_interval = zeros(2,1);
eval(['post_mean = oo.posterior_mean.' type '.' name ';']);
eval(['hpd_interval(1) = oo.posterior_hpdinf.' type '.' name ';']);
eval(['hpd_interval(2) = oo.posterior_hpdsup.' type '.' name ';']);
eval(['post_var = oo.posterior_variance.' type '.' name ';']);
post_mean = oo.posterior_mean.(type).(name);
hpd_interval(1) = oo.posterior_hpdinf.(type).(name);
hpd_interval(2) = oo.posterior_hpdsup.(type).(name);
post_var = oo.posterior_variance.(type).(name);

2
matlab/gsa/log_trans_.m
View File

@ -26,7 +26,7 @@ end
if nargin==1,
xdir0='';
end
f=inline('gsa_skewness(log(y+lam))','lam','y');
f=@(lam,y)gsa_skewness(log(y+lam));
isig=1;
if ~(max(y0)<0 | min(y0)>0)
if gsa_skewness(y0)<0,

39
matlab/mh_optimal_bandwidth.m
View File

@ -21,10 +21,10 @@ function optimal_bandwidth = mh_optimal_bandwidth(data,number_of_draws,bandwidth
% none.
%
% REFERENCES:
% [1] M. Skold and G.O. Roberts [2003], "Density estimation for the Metropolis-Hastings algorithm".
% [1] M. Skoeld and G.O. Roberts [2003], "Density estimation for the Metropolis-Hastings algorithm".
% [2] Silverman [1986], "Density estimation for statistics and data analysis".
% Copyright (C) 2004-2011 Dynare Team
% Copyright (C) 2004-2015 Dynare Team
%
% This file is part of Dynare.
%
@ -44,44 +44,43 @@ function optimal_bandwidth = mh_optimal_bandwidth(data,number_of_draws,bandwidth
%% Kernel specifications.
if strcmpi(kernel_function,'gaussian')
% Kernel definition
k = inline('inv(sqrt(2*pi))*exp(-0.5*x.^2)');
k = @(x)inv(sqrt(2*pi))*exp(-0.5*x.^2);
% Second derivate of the kernel function
k2 = inline('inv(sqrt(2*pi))*(-exp(-0.5*x.^2)+(x.^2).*exp(-0.5*x.^2))');
k2 = @(x)inv(sqrt(2*pi))*(-exp(-0.5*x.^2)+(x.^2).*exp(-0.5*x.^2));
% Fourth derivate of the kernel function
k4 = inline('inv(sqrt(2*pi))*(3*exp(-0.5*x.^2)-6*(x.^2).*exp(-0.5*x.^2)+(x.^4).*exp(-0.5*x.^2))');
k4 = @(x)inv(sqrt(2*pi))*(3*exp(-0.5*x.^2)-6*(x.^2).*exp(-0.5*x.^2)+(x.^4).*exp(-0.5*x.^2));
% Sixth derivate of the kernel function
k6 = inline(['inv(sqrt(2*pi))*(-15*exp(-0.5*x.^2)+45*(x.^2).*exp(-' ...
'0.5*x.^2)-15*(x.^4).*exp(-0.5*x.^2)+(x.^6).*exp(-0.5*x.^2))']);
k6 = @(x)inv(sqrt(2*pi))*(-15*exp(-0.5*x.^2)+45*(x.^2).*exp(-0.5*x.^2)-15*(x.^4).*exp(-0.5*x.^2)+(x.^6).*exp(-0.5*x.^2));
mu02 = inv(2*sqrt(pi));
mu21 = 1;
elseif strcmpi(kernel_function,'uniform')
k = inline('0.5*(abs(x) <= 1)');
k = @(x)0.5*(abs(x) <= 1);
mu02 = 0.5;
mu21 = 1/3;
elseif strcmpi(kernel_function,'triangle')
k = inline('(1-abs(x)).*(abs(x) <= 1)');
k = @(x)(1-abs(x)).*(abs(x) <= 1);
mu02 = 2/3;
mu21 = 1/6;
elseif strcmpi(kernel_function,'epanechnikov')
k = inline('0.75*(1-x.^2).*(abs(x) <= 1)');
k = @(x)0.75*(1-x.^2).*(abs(x) <= 1);
mu02 = 3/5;
mu21 = 1/5;
elseif strcmpi(kernel_function,'quartic')
k = inline('0.9375*((1-x.^2).^2).*(abs(x) <= 1)');
k = @(x)0.9375*((1-x.^2).^2).*(abs(x) <= 1);
mu02 = 15/21;
mu21 = 1/7;
elseif strcmpi(kernel_function,'triweight')
k = inline('1.09375*((1-x.^2).^3).*(abs(x) <= 1)');
k2 = inline('(105/4*(1-x.^2).*x.^2-105/16*(1-x.^2).^2).*(abs(x) <= 1)');
k4 = inline('(-1575/4*x.^2+315/4).*(abs(x) <= 1)');
k6 = inline('(-1575/2).*(abs(x) <= 1)');
k = @(x)1.09375*((1-x.^2).^3).*(abs(x) <= 1);
k2 = @(x)(105/4*(1-x.^2).*x.^2-105/16*(1-x.^2).^2).*(abs(x) <= 1);
k4 = @(x)(-1575/4*x.^2+315/4).*(abs(x) <= 1);
k6 = @(x)(-1575/2).*(abs(x) <= 1);
mu02 = 350/429;
mu21 = 1/9;
elseif strcmpi(kernel_function,'cosinus')
k = inline('(pi/4)*cos((pi/2)*x).*(abs(x) <= 1)');
k2 = inline('(-1/16*cos(pi*x/2)*pi^3).*(abs(x) <= 1)');
k4 = inline('(1/64*cos(pi*x/2)*pi^5).*(abs(x) <= 1)');
k6 = inline('(-1/256*cos(pi*x/2)*pi^7).*(abs(x) <= 1)');
k = @(x)(pi/4)*cos((pi/2)*x).*(abs(x) <= 1);
k2 = @(x)(-1/16*cos(pi*x/2)*pi^3).*(abs(x) <= 1);
k4 = @(x)(1/64*cos(pi*x/2)*pi^5).*(abs(x) <= 1);
k6 = @(x)(-1/256*cos(pi*x/2)*pi^7).*(abs(x) <= 1);
mu02 = (pi^2)/16;
mu21 = (pi^2-8)/pi^2;
else
@ -163,7 +162,7 @@ else
end
optimal_bandwidth = h;
return,
return
function correction = correction_for_repeated_draws(draws,n)