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sur: add model_name option

time-shift
Houtan Bastani 2019-01-24 14:13:01 +01:00
parent 35cabed989
commit 6d447f195a
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1 changed files with 39 additions and 28 deletions
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67
matlab/ols/sur.m
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@ -1,5 +1,5 @@
function varargout = sur(ds, param_names, eqtags) function varargout = sur(ds, param_names, eqtags, model_name)
%function varargout = sur(ds, param_names, eqtags) %function varargout = sur(ds, param_names, eqtags, model_name)
% Seemingly Unrelated Regressions % Seemingly Unrelated Regressions
% %
% INPUTS % INPUTS
@ -7,6 +7,8 @@ function varargout = sur(ds, param_names, eqtags)
% param_names [cellstr] list of parameters to estimate % param_names [cellstr] list of parameters to estimate
% eqtags [cellstr] names of equation tags to estimate. If empty, % eqtags [cellstr] names of equation tags to estimate. If empty,
% estimate all equations % estimate all equations
% model_name [string] name of model to be displayed with
% report
% %
% OUTPUTS % OUTPUTS
% none % none
@ -34,8 +36,16 @@ function varargout = sur(ds, param_names, eqtags)
global M_ oo_ options_ global M_ oo_ options_
%% Check input argument %% Check input argument
if nargin < 1 || nargin > 3 if nargin < 1 || nargin > 4
error('function takes between 1 and 3 arguments'); error('function takes between 1 and 4 arguments');
end
if nargin < 4
if ~isfield(oo_, 'sur')
model_name = 'sur_model_number_1';
else
model_name = ['sur_model_number_' num2str(length(fieldnames(oo_.sur)) + 1)];
end
end end
if nargin < 3 if nargin < 3
@ -114,63 +124,64 @@ for i = 1:length(constrained)
end end
%% Estimation %% Estimation
oo_.sur.dof = nobs; oo_.sur.(model_name).dof = nobs;
% Estimated Parameters % Estimated Parameters
[q, r] = qr(X.data, 0); [q, r] = qr(X.data, 0);
xpxi = (r'*r)\eye(size(X.data, 2)); xpxi = (r'*r)\eye(size(X.data, 2));
resid = Y.data - X.data * (r\(q'*Y.data)); resid = Y.data - X.data * (r\(q'*Y.data));
resid = reshape(resid, oo_.sur.dof, neqs); resid = reshape(resid, oo_.sur.(model_name).dof, neqs);
M_.Sigma_e = resid'*resid/oo_.sur.dof; M_.Sigma_e = resid'*resid/oo_.sur.(model_name).dof;
kLeye = kron(chol(inv(M_.Sigma_e)), eye(oo_.sur.dof)); kLeye = kron(chol(inv(M_.Sigma_e)), eye(oo_.sur.(model_name).dof));
[q, r] = qr(kLeye*X.data, 0); [q, r] = qr(kLeye*X.data, 0);
oo_.sur.beta = r\(q'*kLeye*Y.data); oo_.sur.(model_name).beta = r\(q'*kLeye*Y.data);
M_.params(opidxs) = oo_.sur.beta; M_.params(opidxs) = oo_.sur.(model_name).beta;
% Yhat % Yhat
oo_.sur.Yhat = X.data * oo_.sur.beta; oo_.sur.(model_name).Yhat = X.data * oo_.sur.(model_name).beta;
% Residuals % Residuals
oo_.sur.resid = Y.data - oo_.sur.Yhat; oo_.sur.(model_name).resid = Y.data - oo_.sur.(model_name).Yhat;
% Correct Yhat reported back to user % Correct Yhat reported back to user
oo_.sur.Yhat = oo_.sur.Yhat + lhssub; oo_.sur.(model_name).Yhat = oo_.sur.(model_name).Yhat + lhssub;
%% Calculate statistics %% Calculate statistics
% Estimate for sigma^2 % Estimate for sigma^2
SS_res = oo_.sur.resid'*oo_.sur.resid; SS_res = oo_.sur.(model_name).resid'*oo_.sur.(model_name).resid;
oo_.sur.s2 = SS_res/oo_.sur.dof; oo_.sur.(model_name).s2 = SS_res/oo_.sur.(model_name).dof;
% R^2 % R^2
ym = Y.data - mean(Y.data); ym = Y.data - mean(Y.data);
SS_tot = ym'*ym; SS_tot = ym'*ym;
oo_.sur.R2 = 1 - SS_res/SS_tot; oo_.sur.(model_name).R2 = 1 - SS_res/SS_tot;
% Adjusted R^2 % Adjusted R^2
oo_.sur.adjR2 = oo_.sur.R2 - (1 - oo_.sur.R2)*M_.param_nbr/(oo_.sur.dof - 1); oo_.sur.(model_name).adjR2 = oo_.sur.(model_name).R2 - (1 - oo_.sur.(model_name).R2)*M_.param_nbr/(oo_.sur.(model_name).dof - 1);
% Durbin-Watson % Durbin-Watson
ediff = oo_.sur.resid(2:oo_.sur.dof) - oo_.sur.resid(1:oo_.sur.dof - 1); ediff = oo_.sur.(model_name).resid(2:oo_.sur.(model_name).dof) - oo_.sur.(model_name).resid(1:oo_.sur.(model_name).dof - 1);
oo_.sur.dw = (ediff'*ediff)/SS_res; oo_.sur.(model_name).dw = (ediff'*ediff)/SS_res;
% Standard Error % Standard Error
oo_.sur.stderr = sqrt(oo_.sur.s2*diag(xpxi)); oo_.sur.(model_name).stderr = sqrt(oo_.sur.(model_name).s2*diag(xpxi));
% T-Stat % T-Stat
oo_.sur.tstat = oo_.sur.beta./oo_.sur.stderr; oo_.sur.(model_name).tstat = oo_.sur.(model_name).beta./oo_.sur.(model_name).stderr;
%% Print Output %% Print Output
if ~options_.noprint if ~options_.noprint
preamble = {sprintf('No. Equations: %d', neqs), ... preamble = {['Model name: ' model_name], ...
sprintf('No. Equations: %d', neqs), ...
sprintf('No. Independent Variables: %d', size(X, 2)), ... sprintf('No. Independent Variables: %d', size(X, 2)), ...
sprintf('Observations: %d', oo_.sur.dof)}; sprintf('Observations: %d', oo_.sur.(model_name).dof)};
afterward = {sprintf('R^2: %f', oo_.sur.R2), ... afterward = {sprintf('R^2: %f', oo_.sur.(model_name).R2), ...
sprintf('R^2 Adjusted: %f', oo_.sur.adjR2), ... sprintf('R^2 Adjusted: %f', oo_.sur.(model_name).adjR2), ...
sprintf('s^2: %f', oo_.sur.s2), ... sprintf('s^2: %f', oo_.sur.(model_name).s2), ...
sprintf('Durbin-Watson: %f', oo_.sur.dw)}; sprintf('Durbin-Watson: %f', oo_.sur.(model_name).dw)};
if ~isempty(constrained_param_idxs) if ~isempty(constrained_param_idxs)
afterward = [afterward, ['Constrained parameters: ' ... afterward = [afterward, ['Constrained parameters: ' ...
@ -179,6 +190,6 @@ if ~options_.noprint
dyn_table('SUR Estimation', preamble, afterward, X.name, ... dyn_table('SUR Estimation', preamble, afterward, X.name, ...
{'Estimates','t-statistic','Std. Error'}, 4, ... {'Estimates','t-statistic','Std. Error'}, 4, ...
[oo_.sur.beta oo_.sur.tstat oo_.sur.stderr]); [oo_.sur.(model_name).beta oo_.sur.(model_name).tstat oo_.sur.(model_name).stderr]);
end end
end end