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Added multivariate student as a proposal distribution for the metropolis hastings. 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1743 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2008-03-13 08:27:55 +00:00
parent d6e004e91d
commit 8917d41046
7 changed files with 62 additions and 493 deletions
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4
matlab/dynare_estimation.m
View File

@ -868,9 +868,9 @@ if (any(bayestopt_.pshape >0 ) & options_.mh_replic) | ...
if options_.mh_replic
if ~options_.load_mh_file
if ~options_.bvar_dsge
metropolis('DsgeLikelihood',xparam1,invhess,bounds,gend,data);
random_walk_metropolis_hastings('DsgeLikelihood','rand_multivariate_normal',xparam1,invhess,bounds,gend,data);
else
metropolis('DsgeVarLikelihood',xparam1,invhess,bounds,gend);
random_walk_metropolis_hastings('DsgeVarLikelihood','rand_multivariate_normal',xparam1,invhess,bounds,gend);
end
else
if options_.use_mh_covariance_matrix

10
matlab/global_initialization.m
View File

@ -1,6 +1,4 @@
function global_initialization()
% function global_initialization()
% initializes global variables and options for DYNARE
%
% INPUTS
@ -14,8 +12,6 @@ function global_initialization()
%
% part of DYNARE, copyright Dynare Team (2003-2008)
% Gnu Public License.
global oo_ M_ options_ ct_ endval_ rplottype_
ct_=0;
@ -147,9 +143,10 @@ function global_initialization()
options_.markowitz = 0.5;
options_.simulation_method = 0;
options_.cutoff = 1e-12;
options_.student_degrees_of_freedom = 3;
% Misc
options_.conf_sig = 0.9;
options_.conf_sig = 0.6;
oo_.exo_simul = [];
oo_.endo_simul = [];
oo_.dr = [];
@ -164,5 +161,4 @@ function global_initialization()
M_.bvar = [];
% rplot
options_.dsample = 0;
options_.dsample = 0;

474
matlab/metropolis.m
View File

@ -1,474 +0,0 @@
function metropolis(TargetFun,xparam1,vv,mh_bounds,varargin)
% function metropolis(TargetFun,xparam1,vv,mh_bounds,varargin)
% Metropolis-Hastings algorithm.
%
% INPUTS
% o TargetFun [char] string specifying the name of the objective
% function (posterior kernel).
% o xparam1 [double] (p*1) vector of parameters to be estimated (initial values).
% o vv [double] (p*p) matrix, posterior covariance matrix (at the mode).
% o mh_bounds [double] (p*2) matrix defining lower and upper bounds for the parameters.
% o varargin list of argument following mh_bounds
%
% OUTPUTS
% None
%
% ALGORITHM
% Metropolis-Hastings.
%
% SPECIAL REQUIREMENTS
% None.
%
% part of DYNARE, copyright Dynare Team (2006-2008)
% Gnu Public License.
global M_ options_ bayestopt_
ModelName = M_.fname;
if ~isempty(M_.bvar)
ModelName = [M_.fname '_bvar'];
end
bayestopt_.penalty = 1e8;
MhDirectoryName = CheckPath('metropolis');
nblck = options_.mh_nblck;
nruns = ones(nblck,1)*options_.mh_replic;
npar = length(xparam1);
MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
d = chol(vv);
options_.lik_algo = 1;
OpenOldFile = ones(nblck,1);
if ~options_.load_mh_file & ~options_.mh_recover
%% Here we start a new metropolis-hastings, previous draws are not
%% considered.
if nblck > 1
disp('MH: Multiple chains mode.')
else
disp('MH: One Chain mode.')
end
%% Delete old mh files...
files = dir([ MhDirectoryName '/' ModelName '_mh*_blck*.mat']);
if length(files)
delete([ MhDirectoryName '/' ModelName '_mh*_blck*.mat']);
disp('MH: Old _mh files succesfully erased!')
end
file = dir([ MhDirectoryName '/metropolis.log']);
if length(file)
delete([ MhDirectoryName '/metropolis.log']);
disp('MH: Old metropolis.log file succesfully erased!')
disp('MH: Creation of a new metropolis.log file.')
end
fidlog = fopen([MhDirectoryName '/metropolis.log'],'w');
fprintf(fidlog,'%% MH log file (Dynare).\n');
fprintf(fidlog,['%% ' datestr(now,0) '.\n']);
fprintf(fidlog,' \n\n');
fprintf(fidlog,'%% Session 1.\n');
fprintf(fidlog,' \n');
fprintf(fidlog,[' Number of blocks...............: ' int2str(nblck) '\n']);
fprintf(fidlog,[' Number of simulations per block: ' int2str(nruns(1)) '\n']);
fprintf(fidlog,' \n');
%% Initial values...
if nblck > 1% Case 1: multiple chains
fprintf(fidlog,[' Initial values of the parameters:\n']);
disp('MH: Searching for initial values...')
ix2 = zeros(nblck,npar);
ilogpo2 = zeros(nblck,1);
for j=1:nblck
validate = 0;
init_iter = 0;
trial = 1;
while validate == 0 & trial <= 10
candidate = options_.mh_init_scale*randn(1,npar)*d + transpose(xparam1);
if all(candidate' > mh_bounds(:,1)) & all(candidate' < mh_bounds(:,2))
ix2(j,:) = candidate;
ilogpo2(j) = - feval(TargetFun,ix2(j,:)',varargin{:});
fprintf(fidlog,[' Blck ' int2str(j) ':\n']);
for i=1:length(ix2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(ix2(j,i)) '\n']);
end
fprintf(fidlog,[' logpo2: ' num2str(ilogpo2(j)) '\n']);
j = j+1;
validate = 1;
end
init_iter = init_iter + 1;
if init_iter > 100 & validate == 0
disp(['MH: I couldn''t get a valid initial value in 100 trials.'])
disp(['MH: You should Reduce mh_init_scale...'])
disp(sprintf('MH: Parameter mh_init_scale is equal to %f.',options_.mh_init_scale))
options_.mh_init_scale = input('MH: Enter a new value... ');
trial = trial+1;
end
end
if trial > 10 & ~validate
disp(['MH: I''m unable to find a starting value for block ' int2str(j)])
return
end
end
fprintf(fidlog,' \n');
disp('MH: Initial values found!')
disp(' ')
else% Case 2: one chain (we start from the posterior mode)
fprintf(fidlog,[' Initial values of the parameters:\n']);
candidate = transpose(xparam1);
if all(candidate' > mh_bounds(:,1)) & all(candidate' < mh_bounds(:,2))
ix2 = candidate;
ilogpo2 = - feval(TargetFun,ix2',varargin{:});
disp('MH: Initialization at the posterior mode.')
disp(' ')
fprintf(fidlog,[' Blck ' int2str(1) 'params:\n']);
for i=1:length(ix2(1,:))
fprintf(fidlog,[' ' int2str(i) ':' num2str(ix2(1,i)) '\n']);
end
fprintf(fidlog,[' Blck ' int2str(1) 'logpo2:' num2str(ilogpo2) '\n']);
else
disp('MH: Initialization failed...')
disp('MH: The posterior mode lies outside the prior bounds.')
return
end
fprintf(fidlog,' \n');
end
fprintf(fidlog,' \n');
fblck = 1;
fline = ones(nblck,1);
NewFile = ones(nblck,1);
%%
%% Creation of the mh-history file:
%%
file = dir([MhDirectoryName '/' ModelName '_mh_history.mat']);
if length(files)
delete([ MhDirectoryName '/' ModelName '_mh_history.mat']);
disp('MH: Old mh_history file succesfully erased!')
end
AnticipatedNumberOfFiles = ceil(nruns(1)/MAX_nruns);
AnticipatedNumberOfLinesInTheLastFile = nruns(1) - (AnticipatedNumberOfFiles-1)*MAX_nruns;
record.Nblck = nblck;
record.MhDraws = zeros(1,3);
record.MhDraws(1,1) = nruns(1);
record.MhDraws(1,2) = AnticipatedNumberOfFiles;
record.MhDraws(1,3) = AnticipatedNumberOfLinesInTheLastFile;
record.AcceptationRates = zeros(1,nblck);
record.Seeds.Normal = randn('state');
record.Seeds.Unifor = rand('state');
record.InitialParameters = ix2;
record.InitialLogLiK = ilogpo2;
record.LastParameters = zeros(nblck,npar);
record.LastLogLiK = zeros(nblck,1);
record.LastFileNumber = AnticipatedNumberOfFiles ;
record.LastLineNumber = AnticipatedNumberOfLinesInTheLastFile;
save([MhDirectoryName '/' ModelName '_mh_history'],'record');
fprintf(fidlog,[' CREATION OF THE MH HISTORY FILE!\n\n']);
fprintf(fidlog,[' Expected number of files per block.......: ' int2str(AnticipatedNumberOfFiles) '.\n']);
fprintf(fidlog,[' Expected number of lines in the last file: ' ...
int2str(AnticipatedNumberOfLinesInTheLastFile) '.\n']);
fprintf(fidlog,['\n']);
fprintf(fidlog,[' Initial seed (randn):\n']);
for i=1:length(record.Seeds.Normal)
fprintf(fidlog,[' ' num2str(record.Seeds.Normal(i)') '\n']);
end
fprintf(fidlog,[' Initial seed (rand).:\n']);
for i=1:length(record.Seeds.Unifor)
fprintf(fidlog,[' ' num2str(record.Seeds.Unifor(i)') '\n']);
end
fprintf(fidlog,' \n');
fclose(fidlog);
elseif options_.load_mh_file & ~options_.mh_recover
%% Here we consider previous mh files (previous mh did not crash).
disp('MH: I''m loading past metropolis-hastings simulations...')
file = dir([ MhDirectoryName '/' ModelName '_mh_history.mat' ]);
files = dir([ MhDirectoryName '/' ModelName '_mh*.mat']);
if ~length(files)
disp('MH:: FAILURE! there is no MH file to load here!')
return
end
if ~length(file)
disp('MH:: FAILURE! there is no MH-history file!')
return
else
load([ MhDirectoryName '/' ModelName '_mh_history'])
end
fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
fprintf(fidlog,'\n');
fprintf(fidlog,['%% Session ' int2str(length(record.MhDraws(:,1))+1) '.\n']);
fprintf(fidlog,' \n');
fprintf(fidlog,[' Number of blocks...............: ' int2str(nblck) '\n']);
fprintf(fidlog,[' Number of simulations per block: ' int2str(nruns(1)) '\n']);
fprintf(fidlog,' \n');
past_number_of_blocks = record.Nblck;
if past_number_of_blocks ~= nblck
disp('MH:: The specified number of blocks doesn''t match with the previous number of blocks!')
disp(['MH:: You declared ' int2str(nblck) ' blocks, but the previous number of blocks was ' ...
int2str(past_number_of_blocks) '.'])
disp(['MH:: I will run the Metropolis-Hastings with ' int2str(past_number_of_blocks) ' blocks.' ])
nblck = past_number_of_blocks;
options_.mh_nblck = nblck;
end
% I read the last line of the last mh-file for initialization
% of the new metropolis-hastings simulations:
LastFileNumber = record.LastFileNumber;
LastLineNumber = record.LastLineNumber;
if LastLineNumber < MAX_nruns
NewFile = ones(nblck,1)*LastFileNumber;
else
NewFile = ones(nblck,1)*(LastFileNumber+1);
end
ilogpo2 = record.LastLogLiK;
ix2 = record.LastParameters;
fblck = 1;
fline = ones(nblck,1)*(LastLineNumber+1);
NumberOfPreviousSimulations = sum(record.MhDraws(:,1),1);
record.MhDraws = [record.MhDraws;zeros(1,3)];
NumberOfDrawsWrittenInThePastLastFile = MAX_nruns - LastLineNumber;
NumberOfDrawsToBeSaved = nruns(1) - NumberOfDrawsWrittenInThePastLastFile;
AnticipatedNumberOfFiles = ceil(NumberOfDrawsToBeSaved/MAX_nruns);
AnticipatedNumberOfLinesInTheLastFile = NumberOfDrawsToBeSaved - (AnticipatedNumberOfFiles-1)*MAX_nruns;
record.LastFileNumber = LastFileNumber + AnticipatedNumberOfFiles;
record.LastLineNumber = AnticipatedNumberOfLinesInTheLastFile;
record.MhDraws(end,1) = nruns(1);
record.MhDraws(end,2) = AnticipatedNumberOfFiles;
record.MhDraws(end,3) = AnticipatedNumberOfLinesInTheLastFile;
randn('state',record.Seeds.Normal);
rand('state',record.Seeds.Unifor);
save([MhDirectoryName '/' ModelName '_mh_history'],'record');
disp(['MH: ... It''s done. I''ve loaded ' int2str(NumberOfPreviousSimulations) ' simulations.'])
disp(' ')
fclose(fidlog);
elseif options_.mh_recover
%% The previous metropolis-hastings crashed before the end! I try to
%% recover the saved draws...
disp('MH: Recover mode!')
disp(' ')
file = dir([MhDirectoryName '/' ModelName '_mh_history.mat']);
if ~length(file)
disp('MH:: FAILURE! there is no MH-history file!')
return
else
load([ MhDirectoryName '/' ModelName '_mh_history'])
end
nblck = record.Nblck;
options_.mh_nblck = nblck;
if size(record.MhDraws,1) == 1
OldMh = 0;% The crashed metropolis was the first session.
else
OldMh = 1;% The crashed metropolis wasn't the first session.
end
%% Default initialization:
if OldMh
ilogpo2 = record.LastLogLiK;
ix2 = record.LastParameters;
else
ilogpo2 = record.InitialLogLiK;
ix2 = record.InitialParameters;
end
%% Set "NewFile":
if OldMh
LastLineNumberInThePreviousMh = record.MhDraws(end-1,3);
LastFileNumberInThePreviousMh = sum(record.MhDraws(1:end-1,2),1);
if LastLineNumberInThePreviousMh < MAX_nruns
NewFile = ones(nblck,1)*LastFileNumberInThePreviousMh;
else
NewFile = ones(nblck,1)*(LastFileNumberInThePreviousMh+1);
end
else
NewFile = ones(nblck,1);
end
%% Set fline (First line):
if OldMh
fline = ones(nblck,1)*(LastLineNumberInThePreviousMh+1);
else
fline = ones(nblck,1);
end
%% Set fblck (First block):
fblck = 1;
%% How many mh files should we have ?
ExpectedNumberOfMhFilesPerBlock = sum(record.MhDraws(:,2),1);
ExpectedNumberOfMhFiles = ExpectedNumberOfMhFilesPerBlock*nblck;
%% I count the total number of saved mh files...
AllMhFiles = dir([MhDirectoryName '/' ModelName '_mh*_blck*.mat']);
TotalNumberOfMhFiles = length(AllMhFiles);
%% I count the number of saved mh files per block
NumberOfMhFilesPerBlock = zeros(nblck,1);
for i = 1:nblck
BlckMhFiles = dir([ MhDirectoryName '/' ModelName '_mh*_blck' int2str(i) '.mat']);
NumberOfMhFilesPerBlock(i) = length(BlckMhFiles);
end
tmp = NumberOfMhFilesPerBlock(1);
%% Is there a chain with less mh files than expected ?
CrashedBlck = 1; b = 1;
while b <= nblck
if NumberOfMhFilesPerBlock(b) < ExpectedNumberOfMhFilesPerBlock
CrashedBlck = b;% YES, chain b!
disp(['MH: Chain ' int2str(b) ' is uncomplete!'])
break
else
disp(['MH: Chain ' int2str(b) ' is complete!'])
end
b = b+1;
end
if b>nblck
disp('MH: You probably don''t need to recover a previous crashed metropolis...')
disp(' or Dynare is unable to recover it.')
error('I stop. You should modify your mod file...')
end
%% The new metropolis-hastings should start from chain... (fblck=CrashedBlck)
fblck = CrashedBlck;
%% How many mh-files are saved in this block ?
NumberOfSavedMhFilesInTheCrashedBlck = NumberOfMhFilesPerBlock(CrashedBlck);
%% How many mh-files were saved in this block during the last session
%% (if there was a complete session before the crash)
if OldMh
ante = sum(record.MhDraws(1:end-1,2),1);
NumberOfSavedMhFilesInTheCrashedBlck = NumberOfSavedMhFilesInTheCrashedBlck - ante;
end
%% Is the last mh-file of the previous session full ?
%% (if there was a complete session before the crash)
if OldMh && ~NumberOfSavedMhFilesInTheCrashedBlck
load([MhDirectoryName '/' ModelName '_mh' int2str(ante) '_blck' int2str(CrashedBlck) '.mat'],'logpo2');
if length(logpo2) == MAX_nruns
IsTheLastFileOfThePreviousMhFull = 1;
NumberOfCompletedMhFiles = NumberOfMhFilesPerBlock(CrashedBlck);
reste = 0;
else
IsTheLastFileOfThePreviousMhFull = 0;
NumberOfCompletedMhFiles = ante-1;
reste = MAX_nruns-LastLineNumberInThePreviousMh;
end
elseif OldMh && NumberOfSavedMhFilesInTheCrashedBlck
IsTheLastFileOfThePreviousMhFull = 1;
NumberOfCompletedMhFiles = NumberOfMhFilesPerBlock(CrashedBlck);
reste = 0;
elseif ~OldMh && NumberOfSavedMhFilesInTheCrashedBlck
IsTheLastFileOfThePreviousMhFull = 0;
NumberOfCompletedMhFiles = NumberOfMhFilesPerBlock(CrashedBlck);
reste = 0;
elseif ~OldMh && NumberOfSavedMhFilesInTheCrashedBlck
IsTheLastFileOfThePreviousMhFull = 0;
NumberOfCompletedMhFiles = 0;
reste = 0;
end
%% How many runs were saved ?
NumberOfSavedDraws = MAX_nruns*NumberOfCompletedMhFiles + reste;
%% Here is the number of draws we still need to complete the block:
if OldMh
nruns(CrashedBlck) = nruns(CrashedBlck)-(NumberOfSavedDraws-sum(record.MhDraws(1:end-1,1)));
end
%% I've got all the needed information... I can initialize the MH:
if OldMh
if NumberOfSavedMhFilesInTheCrashedBlck
load([MhDirectoryName '/' ModelName '_mh' ...
int2str(NumberOfCompletedMhFiles) '_blck' int2str(CrashedBlck) '.mat']);
fline(CrashedBlck,1) = 1;
NewFile(CrashedBlck) = NumberOfCompletedMhFiles+1;% NumberOfSavedMhFilesInTheCrashedBlck+1;
else
load([MhDirectoryName '/' ModelName '_mh' ...
int2str(ante) '_blck' int2str(CrashedBlck) '.mat']);
if reste
fline(CrashedBlck,1) = length(logpo2)+1;
NewFile(CrashedBlck) = LastFileNumberInThePreviousMh;
else
fline(CrashedBlck,1) = 1;
NewFile(CrashedBlck) = LastFileNumberInThePreviousMh+1;
end
end
ilogpo2(CrashedBlck) = logpo2(end);
ix2(CrashedBlck,:) = x2(end,:);
end
end% of (if options_.load_mh_file == {0,1 or -1})
%%%%
%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
%%%%
InitSizeArray = min([MAX_nruns*ones(nblck) nruns],[],2);
for b = fblck:nblck
if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
'_blck' int2str(b) '.mat'])
x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
OpenOldFile(b) = 0;
else
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
end
hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(nblck) ')...']);
set(hh,'Name','Metropolis-Hastings');
isux = 0;
jsux = 0;
irun = fline(b);
j = 1;
while j <= nruns(b)
par = randn(1,npar)*d;
par = par.*bayestopt_.jscale' + ix2(b,:);
if all(par'>mh_bounds(:,1)) & all(par'<mh_bounds(:,2))
logpost = - feval(TargetFun,par',varargin{:});
else
logpost = -inf;
end
if (logpost > -inf) & (log(rand) < logpost-ilogpo2(b))
x2(irun,:) = par;
ix2(b,:) = par;
logpo2(irun) = logpost;
ilogpo2(b) = logpost;
isux = isux + 1;
jsux = jsux + 1;
else
x2(irun,:) = ix2(b,:);
logpo2(irun) = ilogpo2(b);
end
prtfrc = j/nruns(b);
waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations
save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b)],'x2','logpo2');
InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
fprintf(fidlog,['\n']);
fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
fprintf(fidlog,' \n');
fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
fprintf(fidlog,[' Posterior mean........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
fprintf(fidlog,[' Minimum value.........:\n']);;
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
fprintf(fidlog,[' Maximum value.........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
fprintf(fidlog,' \n');
fclose(fidlog);
jsux = 0;
if j == nruns(b) % I record the last draw...
record.LastParameters(b,:) = x2(end,:);
record.LastLogLiK(b) = logpo2(end);
end
if InitSizeArray(b)
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
NewFile(b) = NewFile(b) + 1;
irun = 0;
else% InitSizeArray is equal to zero because we are at the end of an mc chain.
InitSizeArray(b) = min(nruns(b),MAX_nruns);
end
end
j=j+1;
irun = irun + 1;
end% End of the simulations for one mh-block.
record.AcceptationRates(b) = isux/j;
close(hh);
end% End of the loop over the mh-blocks.
record.Seeds.Normal = randn('state');
record.Seeds.Unifor = rand('state');
save([MhDirectoryName '/' ModelName '_mh_history'],'record');
disp(['MH: Number of mh files : ' int2str(NewFile(1)) ' per block.'])
disp(['MH: Total number of generated files : ' int2str(NewFile(1)*nblck) '.'])
disp(['MH: Total number of iterations : ' int2str((NewFile(1)-1)*MAX_nruns+irun-1) '.'])
disp(' ')

6
matlab/metropolis_hastings_initialization.m
View File

@ -75,9 +75,9 @@ if ~options_.load_mh_file & ~options_.mh_recover
validate = 0;
init_iter = 0;
trial = 1;
while validate == 0 & trial <= 10
candidate = options_.mh_init_scale*randn(1,npar)*d + transpose(xparam1);
if all(candidate' > mh_bounds(:,1)) & all(candidate' < mh_bounds(:,2))
while validate == 0 & trial <= 10
candidate = rand_multivariate_normal( transpose(xparam1), d * options_.mh_init_scale, npar);
if all(candidate(:) > mh_bounds(:,1)) & all(candidate(:) < mh_bounds(:,2))
ix2(j,:) = candidate;
ilogpo2(j) = - feval(TargetFun,ix2(j,:)',varargin{:});
fprintf(fidlog,[' Blck ' int2str(j) ':\n']);

19
matlab/rand_multivariate_normal.m Normal file
View File

@ -0,0 +1,19 @@
function draw = rand_multivariate_normal(Mean,Sigma_upper_chol,n)
% Pseudo random draws from a multivariate normal distribution,
% \mathcal N_n(Mean,Sigma), with expectation Mean and variance Sigma.
%
% INPUTS
%
% Mean [double] 1*n vector, expectation of the multivariate random variable.
% Sigma_upper_chol [double] n*n matrix, upper triangular Cholesky decomposition of Sigma (the covariance matrix).
% n [integer] dimension.
%
% OUTPUTS
% draw [double] 1*n vector drawn from a multivariate normal distribution with expectation Mean and
% covariance Sigma
%
% SPECIAL REQUIREMENTS
%
% part of DYNARE, copyright Dynare Team (2003-2008)
% Gnu Public License.
draw = Mean + randn(1,n) * Sigma_upper_chol;

23
matlab/rand_multivariate_student.m Normal file
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@ -0,0 +1,23 @@
function draw = rand_multivariate_student(Mean,Sigma_upper_chol,df)
% Pseudo random draws from a multivariate student distribution,
% with expectation Mean, variance Sigma*df/(df-2) and degrees of freedom df>0.
%
% INPUTS
%
% Mean [double] 1*n vector, expectation of the multivariate random variable.
% Sigma_upper_chol [double] n*n matrix, upper triangular Cholesky decomposition of Sigma
% (the covariance matrix up to a factor df/(df-2)).
% df [integer] degrees of freedom.
%
% OUTPUTS
% draw [double] 1*n vector drawn from a multivariate normal distribution with expectation Mean and
% covariance Sigma.
%
% REMARK This is certainly not the most efficient way...
%
% NOTE See Zellner (appendix B.2, 1971) for a definition.
%
% part of DYNARE, copyright Dynare Team (2003-2008)
% Gnu Public License.
n = length(Mean);
draw = Mean + randn(1,n) * Sigma_upper_chol * sqrt(df/sum(randn(df,1).^2));

19
matlab/random_walk_metropolis_hastings.m
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@ -1,4 +1,4 @@
function random_walk_metropolis_hastings(TargetFun,xparam1,vv,mh_bounds,varargin)
function random_walk_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bounds,varargin)
% Random walk Metropolis-Hastings algorithm.
%
% INPUTS
@ -25,14 +25,20 @@ global M_ options_ bayestopt_
%%%% Initialization of the random walk metropolis-hastings chains.
%%%%
[ ix2, ilogpo2, ModelName, MhDirectoryName, fblck, fline, npar, nblck, nruns, NewFile, MAX_nruns, d ] = ...
metropolis_hastings_initialization(TargetFun,xparam1,vv,mh_bounds,varargin{:});
metropolis_hastings_initialization(TargetFun, xparam1, vv, mh_bounds, varargin{:});
options_.lik_algo = 1;
OpenOldFile = ones(nblck,1);
if strcmpi(ProposalFun,'rand_multivariate_normal')
n = npar;
elseif strcmpi(ProposalFun,'rand_multivariate_student')
n = options_.student_degrees_of_freedom;
end
load([MhDirectoryName '/' ModelName '_mh_history'],'record');
%%%%
%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
%%%%
InitSizeArray = min([MAX_nruns*ones(nblck) nruns],[],2);
jscale = diag(bayestopt_.jscale);
for b = fblck:nblck
if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
@ -51,15 +57,14 @@ for b = fblck:nblck
irun = fline(b);
j = 1;
while j <= nruns(b)
par = randn(1,npar)*d;
par = par.*bayestopt_.jscale' + ix2(b,:);
if all(par'>mh_bounds(:,1)) & all(par'<mh_bounds(:,2))
logpost = - feval(TargetFun,par',varargin{:});
par = feval(ProposalFun, ix2(b,:), d * jscale, n);
if all( par(:) > mh_bounds(:,1) ) & all( par(:) < mh_bounds(:,2) )
logpost = - feval(TargetFun, par(:), varargin{:});
else
logpost = -inf;
end
if (logpost > -inf) & (log(rand) < logpost-ilogpo2(b))
x2(irun,:) = par;
x2(irun,:) = par;
ix2(b,:) = par;
logpo2(irun) = logpost;
ilogpo2(b) = logpost;