correcting headers of all Kalman filter functions: returns MINUS loglikelihood

matlab/kalman/likelihood/diffuse_kalman_filter.m

@@ -15,7 +15,7 @@ function [LIK, lik] = diffuse_kalman_filter(T,R,Q,H,Pinf,Pstar,Y,start,Z,kalman_
 %    riccati_tol [double]      scalar, tolerance parameter (riccati iteration).
 %             
 % OUTPUTS
-%    LIK:    likelihood
+%    LIK:    MINUS loglikelihood
 %    lik:    density vector in each period
 %        
 % REFERENCES

matlab/kalman/likelihood/kalman_filter.m

@@ -14,7 +14,7 @@ function [LIK, lik] = kalman_filter(T,R,Q,H,P,Y,start,mf,kalman_tol,riccati_tol)
 %    riccati_tol            [double]    scalar, tolerance parameter (riccati iteration).
 %
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %
 % REFERENCES

matlab/kalman/likelihood/missing_observations_diffuse_kalman_filter.m

@@ -19,7 +19,7 @@ function [LIK, lik] = missing_observations_diffuse_kalman_filter(T,R,Q,H,Pinf,Ps
 %    no_more_missing_observations [integer]   scalar.
 %             
 % OUTPUTS
-%    LIK:    likelihood
+%    LIK:    MINUS loglikelihood
 %    lik:    density vector in each period
 %        
 % REFERENCES

matlab/kalman/likelihood/missing_observations_kalman_filter.m

@@ -18,7 +18,7 @@ function  [LIK, lik] = missing_observations_kalman_filter(T,R,Q,H,P,Y,start,mf,k
 %    no_more_missing_observations [integer]   scalar.    
 %    
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %        
 % REFERENCES

matlab/kalman/likelihood/univariate_diffuse_kalman_filter.m

@@ -17,7 +17,7 @@ function [LIK, lik] = univariate_diffuse_kalman_filter(T,R,Q,H,Pinf,Pstar,Y,star
 %    no_more_missing_observations [integer]   scalar.
 %
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %
 % REFERENCES

matlab/kalman/likelihood/univariate_diffuse_kalman_filter_corr.m

@@ -18,7 +18,7 @@ function [LIK, lik] = univariate_diffuse_kalman_filter_corr(T,R,Q,H,Pinf,Pstar,Y
 %    no_more_missing_observations [integer]   scalar.
 %
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %
 % REFERENCES

matlab/kalman/likelihood/univariate_kalman_filter.m

@@ -17,7 +17,7 @@ function [LIK, lik] = univariate_kalman_filter(T,R,Q,H,P,Y,start,mf,kalman_tol,r
 %    no_more_missing_observations [integer]   scalar.
 %
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %
 % REFERENCES

matlab/kalman/likelihood/univariate_kalman_filter_corr.m

@@ -19,7 +19,7 @@ function [LIK, lik] = ...
 %    no_more_missing_observations [integer]   scalar.
 %
 % OUTPUTS
-%    LIK        [double]    scalar, likelihood
+%    LIK        [double]    scalar, MINUS loglikelihood
 %    lik        [double]    vector, density of observations in each period.
 %
 % REFERENCES