Commit 1df8bf15 authored by Johannes Pfeifer's avatar Johannes Pfeifer
Browse files

Bugfix in rplot + typo correction

parent 4b095c2c
function [LIK, LIKK, a, P] = kalman_filter(Y,start,last,a,P,kalman_tol,riccati_tol,presample,T,Q,R,H,Z,mm,pp,rr,Zflag,diffuse_periods,analytic_derivation,DT,DYss,DOm,DH,DP,D2T,D2Yss,D2Om,D2H,D2P)
% Computes the likelihood of a stationnary state space model.
% Computes the likelihood of a stationary state space model.
%! @deftypefn {Function File} {[@var{LIK},@var{likk},@var{a},@var{P} ] =} DsgeLikelihood (@var{Y}, @var{start}, @var{last}, @var{a}, @var{P}, @var{kalman_tol}, @var{riccati_tol},@var{presample},@var{T},@var{Q},@var{R},@var{H},@var{Z},@var{mm},@var{pp},@var{rr},@var{Zflag},@var{diffuse_periods})
......@@ -15,7 +15,7 @@ function [dLIK,dlik,a,Pstar] = kalman_filter_d(Y, start, last, a, Pinf, Pstar, k
% R [double] mm*rr matrix relating the structural innovations to the state vector.
% Q [double] rr*rr covariance matrix of the structural innovations.
% H [double] pp*pp covariance matrix of the measurement errors (if H is equal to zero (scalar) there is no measurement error).
% Z [double] pp*mm matrix, selection matrix or pp linear independant combinations of the state vector.
% Z [double] pp*mm matrix, selection matrix or pp linear independent combinations of the state vector.
% mm [integer] scalar, number of state variables.
% pp [integer] scalar, number of observed variables.
% rr [integer] scalar, number of structural innovations.
......@@ -85,10 +85,11 @@ elseif rplottype == 2
subplot(nl,nc,j) ;
plot(ix(i),y(j,i)) ;
hold on ;
plot(ix(i),oo_.steady_state(j)*ones(1,size(i,1)),'w:') ;
plot(ix(i),oo_.steady_state(strmatch(s1(j,:),M_.endo_names,'exact'))*ones(1,size(i,1)),'r:') ;
xlabel('Periods') ;
ylabel([s1(j,:)],'Interpreter','none') ;
title(['Plot of ' s1(j,:)],'Interpreter','none') ;
axis tight;
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