From e9c15290d3f0feb4672d12610f8a1af94a5a5956 Mon Sep 17 00:00:00 2001 From: Houtan Bastani <houtan.bastani@ens.fr> Date: Tue, 31 Jan 2012 10:21:23 +0100 Subject: [PATCH] remove files of the form *.sav --- MatlabFiles/ERRORS.sav | 86 ------------------------------------------ 1 file changed, 86 deletions(-) delete mode 100755 MatlabFiles/ERRORS.sav diff --git a/MatlabFiles/ERRORS.sav b/MatlabFiles/ERRORS.sav deleted file mode 100755 index 7103d6f..0000000 --- a/MatlabFiles/ERRORS.sav +++ /dev/null @@ -1,86 +0,0 @@ -function [vd,str,imf] = errors(Bh,swish,nn) -% Computing variance decompositions and impulse functions with -% [vd,str,imf] = errors(Bh,swish,nn) -% where imf and vd is of the same format as in RATS, that is to say: -% Column: nvar responses to 1st shock, -% nvar responses to 2nd shock, and so on. -% Row: steps of impulse responses. -% vd: variance decompositions -% str: standard errors of each variable, steps-by-nvar -% imf: impulse response functions -% Bh is the estimated reduced form coefficient in the form -% Y(T*nvar) = XB + U, X: T*k, B: k*nvar. The matrix -% form or dimension is the same as "Bh" from the function "sye"; -% swish is the inv(A0) in the structural model A(L)y(t) = e(t). -% nn is the numbers of inputs [nvar,lags,# of impulse responses]. - -nvar = nn(1); -lags = nn(2); -imstep = nn(3); % number of steps for impulse responses - -Ah = Bh'; -% Row: nvar equations -% Column: 1st lag (with nvar variables) to lags (with nvar variables) + const = k. - -imf = zeros(imstep,nvar*nvar); -vd = imf; -% Column: nvar responses to 1st shock, nvar responses to 2nd shock, and so on. -% Row: steps of impulse responses. -str = zeros(imstep,nvar); % initializing standard errors of each equation -M = zeros(nvar*(lags+1),nvar); -% Stack lags M's in the order of, e.g., [Mlags, ..., M2,M1;M0] -M(1:nvar,:) = swish; -Mtem = M(1:nvar,:); % temporary M -- impulse responses. -% -Mvd = Mtem.^2; % saved for the cumulative sum later -Mvds = (sum(Mvd'))'; -str(1,:) = sqrt(Mvds'); % standard errors of each equation -Mvds = Mvds(:,ones(size(Mvds,1),1)); -Mvdtem = (100.0*Mvd) ./ Mvds; % tempoary Mvd -- variance decompositions -% first or initial responses to -% one standard deviation shock (or forecast errors). -% Row: responses; Column: shocks -% -% * put in the form of "imf" -imf(1,:) = Mtem(:)'; -vd(1,:) = Mvdtem(:)'; - -t = 1; -ims1 = min([imstep-1 lags]); -while t <= ims1 - Mtem = Ah(:,1:nvar*t)*M(1:nvar*t,:); - % Row: nvar equations, each for the nvar variables at tth lag - M(nvar+1:nvar*(t+1),:)=M(1:nvar*t,:); - M(1:nvar,:) = Mtem; - % ** impulse response functions - imf(t+1,:) = Mtem(:)'; - % stack imf with each step, Row: 6 var to 1st shock, 6 var to 2nd shock, etc. - % ** variance decompositions - Mvd = Mvd + Mtem.^2; % saved for the cumulative sum later - Mvds = (sum(Mvd'))'; - str(t+1,:) = sqrt(Mvds'); % standard errors of each equation - Mvds = Mvds(:,ones(size(Mvds,1),1)); - Mvdtem = (100.0*Mvd) ./ Mvds; % tempoary Mvd -- variance decompositions - vd(t+1,:) = Mvdtem(:)'; - % stack vd with each step, Row: 6 var to 1st shock, 6 var to 2nd shock, etc. - t= t+1; -end - -for t = lags+1:imstep-1 - Mtem = Ah(:,1:nvar*lags)*M(1:nvar*lags,:); - % Row: nvar equations, each for the nvar variables at tth lag - M(nvar+1:nvar*(t+1),:) = M(1:nvar*t,:); - M(1:nvar,:)=Mtem; - % ** impulse response functions - imf(t+1,:) = Mtem(:)'; - % stack imf with each step, Row: 6 var to 1st shock, 6 var to 2nd shock, etc. - % ** variance decompositions - Mvd = Mvd + Mtem.^2; % saved for the cumulative sum later - Mvds = (sum(Mvd'))'; - str(t+1,:) = sqrt(Mvds'); % standard errors of each equation - Mvds = Mvds(:,ones(size(Mvds,1),1)); - Mvdtem = (100.0*Mvd) ./ Mvds; % tempoary Mvd -- variance decompositions - vd(t+1,:) = Mvdtem(:)'; - % stack vd with each step, Row: 6 var to 1st shock, 6 var to 2nd shock, etc. -end - \ No newline at end of file -- GitLab