From 8359b90cdf3396769236e9a56eb53ac7862d926c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Scylla=29?=
<stephane.adjemian@univ-lemans.fr>
Date: Thu, 30 Jan 2014 13:00:25 +0100
Subject: [PATCH] Cosmetic changes.
---
matlab/DsgeSmoother.m | 2 +-
matlab/PosteriorFilterSmootherAndForecast.m | 6 +++---
matlab/dr_block.m | 2 +-
matlab/dynare_sensitivity.m | 2 +-
matlab/k_order_pert.m | 3 +--
matlab/prior_posterior_statistics_core.m | 6 +++---
matlab/stochastic_solvers.m | 6 ++----
7 files changed, 12 insertions(+), 15 deletions(-)
diff --git a/matlab/DsgeSmoother.m b/matlab/DsgeSmoother.m
index 51dab6569e..e8e76f97e0 100644
--- a/matlab/DsgeSmoother.m
+++ b/matlab/DsgeSmoother.m
@@ -74,7 +74,7 @@ bayestopt_.mf = bayestopt_.smoother_mf;
if options_.noconstant
constant = zeros(nobs,1);
else
- if options_.loglinear == 1
+ if options_.loglinear
constant = log(SteadyState(bayestopt_.mfys));
else
constant = SteadyState(bayestopt_.mfys);
diff --git a/matlab/PosteriorFilterSmootherAndForecast.m b/matlab/PosteriorFilterSmootherAndForecast.m
index d39d67d35d..0b3bd1e350 100644
--- a/matlab/PosteriorFilterSmootherAndForecast.m
+++ b/matlab/PosteriorFilterSmootherAndForecast.m
@@ -170,19 +170,19 @@ for b=1:B
horizon+maxlag,1);
end
yf(:,IdObs) = yf(:,IdObs)+(gend+[1-maxlag:horizon]')*trend_coeff';
- if options_.loglinear == 1
+ if options_.loglinear
yf = yf+repmat(log(SteadyState'),horizon+maxlag,1);
else
yf = yf+repmat(SteadyState',horizon+maxlag,1);
end
yf1 = forcst2(yyyy,horizon,dr,1);
- if options_.prefilter == 1
+ if options_.prefilter
yf1(:,IdObs,:) = yf1(:,IdObs,:)+ ...
repmat(bayestopt_.mean_varobs',[horizon+maxlag,1,1]);
end
yf1(:,IdObs,:) = yf1(:,IdObs,:)+repmat((gend+[1-maxlag:horizon]')* ...
trend_coeff',[1,1,1]);
- if options_.loglinear == 1
+ if options_.loglinear
yf1 = yf1 + repmat(log(SteadyState'),[horizon+maxlag,1,1]);
else
yf1 = yf1 + repmat(SteadyState',[horizon+maxlag,1,1]);
diff --git a/matlab/dr_block.m b/matlab/dr_block.m
index 6a707f45b8..1878d572ce 100644
--- a/matlab/dr_block.m
+++ b/matlab/dr_block.m
@@ -628,7 +628,7 @@ for i = 1:Size;
- if options_.loglinear == 1
+ if options_.loglinear
error('log linear option is for the moment not supported in first order approximation for a block decomposed mode');
% k = find(dr.kstate(:,2) <= M_.maximum_endo_lag+1);
% klag = dr.kstate(k,[1 2]);
diff --git a/matlab/dynare_sensitivity.m b/matlab/dynare_sensitivity.m
index e4df56984c..4b106f2efa 100644
--- a/matlab/dynare_sensitivity.m
+++ b/matlab/dynare_sensitivity.m
@@ -388,7 +388,7 @@ if options_gsa.glue,
gend = options_.nobs;
rawdata = read_variables(options_.datafile,options_.varobs,[],options_.xls_sheet,options_.xls_range);
rawdata = rawdata(options_.first_obs:options_.first_obs+gend-1,:);
- if options_.loglinear == 1
+ if options_.loglinear
rawdata = log(rawdata);
end
if options_.prefilter == 1
diff --git a/matlab/k_order_pert.m b/matlab/k_order_pert.m
index 315c4494a8..db1ef91f48 100644
--- a/matlab/k_order_pert.m
+++ b/matlab/k_order_pert.m
@@ -97,11 +97,10 @@ else
dr.ghx = dr.g_1(:,1:nspred);
dr.ghu = dr.g_1(:,nspred+1:end);
- if options.loglinear == 1
+ if options.loglinear
k = find(dr.kstate(:,2) <= M.maximum_endo_lag+1);
klag = dr.kstate(k,[1 2]);
k1 = dr.order_var;
-
dr.ghx = repmat(1./dr.ys(k1),1,size(dr.ghx,2)).*dr.ghx.* ...
repmat(dr.ys(k1(klag(:,1)))',size(dr.ghx,1),1);
dr.ghu = repmat(1./dr.ys(k1),1,size(dr.ghu,2)).*dr.ghu;
diff --git a/matlab/prior_posterior_statistics_core.m b/matlab/prior_posterior_statistics_core.m
index f7eaa6f28e..41b5b6d33f 100644
--- a/matlab/prior_posterior_statistics_core.m
+++ b/matlab/prior_posterior_statistics_core.m
@@ -195,12 +195,12 @@ for b=fpar:B
if horizon
yyyy = alphahat(iendo,i_last_obs);
yf = forcst2a(yyyy,dr,zeros(horizon,exo_nbr));
- if options_.prefilter == 1
+ if options_.prefilter
yf(:,IdObs) = yf(:,IdObs)+repmat(bayestopt_.mean_varobs', ...
horizon+maxlag,1);
end
yf(:,IdObs) = yf(:,IdObs)+(gend+[1-maxlag:horizon]')*trend_coeff';
- if options_.loglinear == 1
+ if options_.loglinear
yf = yf+repmat(log(SteadyState'),horizon+maxlag,1);
else
yf = yf+repmat(SteadyState',horizon+maxlag,1);
@@ -212,7 +212,7 @@ for b=fpar:B
end
yf1(:,IdObs,:) = yf1(:,IdObs,:)+repmat((gend+[1-maxlag:horizon]')* ...
trend_coeff',[1,1,1]);
- if options_.loglinear == 1
+ if options_.loglinear
yf1 = yf1 + repmat(log(SteadyState'),[horizon+maxlag,1,1]);
else
yf1 = yf1 + repmat(SteadyState',[horizon+maxlag,1,1]);
diff --git a/matlab/stochastic_solvers.m b/matlab/stochastic_solvers.m
index 0d4827c331..dd835e2ba6 100644
--- a/matlab/stochastic_solvers.m
+++ b/matlab/stochastic_solvers.m
@@ -297,22 +297,20 @@ if M_.exo_det_nbr > 0
kron(hudi,Eud)+dr.ghxud{i-1}(kf,:)* ...
kron(hudj,Eud)+dr.ghxx(kf,:)*kron(hudj,hudi))-M1*R2;
end
-
end
end
end
-if options_.loglinear == 1
+if options_.loglinear
% this needs to be extended for order=2,3
k = find(dr.kstate(:,2) <= M_.maximum_endo_lag+1);
klag = dr.kstate(k,[1 2]);
k1 = dr.order_var;
-
dr.ghx = repmat(1./dr.ys(k1),1,size(dr.ghx,2)).*dr.ghx.* ...
repmat(dr.ys(k1(klag(:,1)))',size(dr.ghx,1),1);
dr.ghu = repmat(1./dr.ys(k1),1,size(dr.ghu,2)).*dr.ghu;
if options_.order>1
- error('Loglinear options currently only works at order 1')
+ error('Loglinear options currently only works at order 1')
end
end
--
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