Provide interface to original PATH files and document how to obtain them
Johannes Pfeifer
Stéphane Adjemian (Lupi)
parent
8f689ce8d2
commit
2751ab08bb
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@ -2984,8 +2984,14 @@ option, @pxref{Model declaration})
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Trust-region algorithm on the entire model.
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@item 10
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Levenberg-Marquardt mixed complementarity problem (LMMCP) solver
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Levenberg-Marquardt mixed compleproblem (LMMCP) solver
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(@cite{Kanzow and Petra 2004})
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@item 11
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PATH 3.0 solver of @cite{Ferris and Munson (1999)}. Dynare only provides the interface
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for using the solver. Due to licence restrictions, you have to download the solver yourself
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from @url{http://pages.cs.wisc.edu/~ferris/path.html} and place it in Matlab's search path.
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@end table
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@noindent
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@ -13950,6 +13956,10 @@ Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood,''
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Fernández-Villaverde, Jesús (2010): ``The econometrics of DSGE models,''
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@i{SERIEs}, 1, 3--49
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@item
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Ferris, Michael C. and Todd S. Munson (1999): ``Interfaces to PATH 3.0: Design, Implementation and Usage'',
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@i{Computational Optimization and Applications}, 12(1), 207--227
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@item
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Geweke, John (1992): ``Evaluating the accuracy of sampling-based approaches
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to the calculation of posterior moments,'' in J.O. Berger, J.M. Bernardo,
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@ -207,9 +207,12 @@ elseif options.solve_algo == 11
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global mcp_data
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mcp_data.func = func;
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mcp_data.args = varargin;
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[x,fval,jac,mu,status] = pathmcp(x,omcppath.lb,omcppath.ub,'mcp_func',omcppath.A,omcppath.b,omcppath.t,omcppath.mu0);
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info = ~status;
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info=0;
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try
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[x,fval,jac,mu] = pathmcp(x,omcppath.lb,omcppath.ub,'mcp_func',omcppath.A,omcppath.b,omcppath.t,omcppath.mu0);
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catch
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info = 1;
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end
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else
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error('DYNARE_SOLVE: option solve_algo must be one of [0,1,2,3,4,9,10,11]')
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end
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172
matlab/pathlcp.m
172
matlab/pathlcp.m
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@ -1,172 +0,0 @@
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function [z,mu,status] = pathlcp(M,q,l,u,z,A,b,t,mu)
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% pathlcp(M,q,l,u,z,A,b,t,mu)
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%
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% Solve the standard linear complementarity problem using PATH:
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% z >= 0, Mz + q >= 0, z'*(Mz + q) = 0
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%
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% Required input:
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% M(n,n) - matrix
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% q(n) - vector
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%
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% Output:
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% z(n) - solution
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% mu(m) - multipliers (if polyhedral constraints are present)
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%
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% Optional input:
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% l(n) - lower bounds default: zero
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% u(n) - upper bounds default: infinity
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% z(n) - starting point default: zero
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% A(m,n) - polyhedral constraint matrix default: empty
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% b(m) - polyhedral right-hand side default: empty
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% t(m) - type of polyhedral constraint default: 1
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% < 0: less than or equal
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% 0: equation
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% > 0: greater than or equal
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% mu(m) - starting value for multipliers default: zero
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%
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% The optional lower and upper bounds are used to define a linear mixed
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% complementarity problem (box constrained variational inequality).
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% l <= z <= u
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% where l_i < z_i < u_i => (Mz + q)_i = 0
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% l_i = z => (Mz + q)_i >= 0
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% u_i = z => (Mz + q)_i <= 0
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%
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% The optional constraints are used to define a polyhedrally constrained
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% variational inequality. These are transformed internally to a standard
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% mixed complementarity problem. The polyhedral constraints are of the
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% form
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% Ax ? b
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% where ? can be <=, =, or >= depending on the type specified for each
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% constraint.
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Big = 1e20;
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if (nargin < 2)
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error('two input arguments required for lcp(M, q)');
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end
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if (~issparse(M))
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M = sparse(M); % Make sure M is sparse
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end
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q = full(q(:)); % Make sure q is a column vector
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[mm,mn] = size(M); % Get the size of the inputs
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n = length(q);
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if (mm ~= mn | mm ~= n)
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error('dimensions of M and q must match');
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end
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if (n == 0)
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error('empty model');
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end
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if (nargin < 3 | isempty(l))
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l = zeros(n,1);
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end
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if (nargin < 4 | isempty(u))
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u = Big*ones(n,1);
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end
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if (nargin < 5 | isempty(z))
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z = zeros(n,1);
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end
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z = full(z(:)); l = full(l(:)); u = full(u(:));
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if (length(z) ~= n | length(l) ~= n | length(u) ~= n)
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error('Input arguments are of incompatible sizes');
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end
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l = max(l,-Big*ones(n,1));
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u = min(u,Big*ones(n,1));
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z = min(max(z,l),u);
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m = 0;
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if (nargin > 5)
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if (nargin < 7)
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error('Polyhedral constraints require A and b');
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end
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if (~issparse(A))
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A = sparse(A);
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end
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b = full(b(:));
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m = length(b);
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if (m > 0)
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[am, an] = size(A);
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if (am ~= m | an ~= n)
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error('Polyhedral constraints of incompatible sizes');
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end
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if (nargin < 8 | isempty(t))
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t = ones(m,1);
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end
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if (nargin < 9 | isempty(mu))
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mu = zeros(m,1);
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end
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t = full(t(:)); mu = full(mu(:));
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if (length(t) ~= m | length(mu) ~= m)
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error('Polyhedral input arguments are of incompatible sizes');
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end
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l_p = -Big*ones(m,1);
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u_p = Big*ones(m,1);
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idx = find(t > 0);
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if (length(idx) > 0)
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l_p(idx) = zeros(length(idx),1);
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end
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idx = find(t < 0);
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if (length(idx) > 0)
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u_p(idx) = zeros(length(idx),1);
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end
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mu = min(max(mu,l_p),u_p);
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M = [M -A'; A sparse(m,m)];
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q = [q; -b];
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z = [z; mu];
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l = [l; l_p];
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u = [u; u_p];
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else
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if (nargin >= 9 & ~isempty(mu))
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error('No polyhedral constraints -- multipliers set.');
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end
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if (nargin >= 8 & ~isempty(t))
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error('No polyhedral constraints -- equation types set.');
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end
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end
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end
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idx = find(l > u);
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if length(idx) > 0
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error('Bounds infeasible.');
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end
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nnzJ = nnz(M);
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[status, ttime] = lcppath(n+m, nnzJ, z, l, u, M, q);
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%if (status ~= 1)
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% status,
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% error('Path fails to solve problem');
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%end
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mu = [];
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if (m > 0)
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mu = z(n+1:n+m);
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z = z(1:n);
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end
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return;
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197
matlab/pathmcp.m
197
matlab/pathmcp.m
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@ -1,197 +0,0 @@
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function [z,f,J,mu,status] = pathmcp(z,l,u,cpfj,A,b,t,mu)
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% pathmcp(z,l,u,cpfj,A,b,t,mu)
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%
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% Solve a polyhedrally constrained variational inequality using PATH
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%
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% Calling syntax: [z,f,J] = pathmcp(z,l,u,cpfunjac,A,b,t,mu)
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%
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% Input:
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% z - starting point
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% l - lower bounds on z
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% u - upper bounds on z
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%
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% cpfunjac - the name of the m-file for evaluating the function F and its
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% Jacobian J (without .m-extension).
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%
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% The following m-file must be supplied (where default name is
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% 'mcp_funjac.m' unless stated otherwise in the variable cpfunjac).
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%
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% 'mcp_funjac.m' contains function [f,J,domerr]=cpfunjac(z,jacflag)
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% that computes the function F and if jacflag=1 the sparse
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% Jacobian J at the point z. domerr returns the number of domain
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% violations.
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%
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% A - constraint matrix
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% b - right hand side of the constraints
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% t - types of the constraints
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% <0 : less than or equal
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% =0 : equal to
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% >0 : greater than or equal
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%
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% We have Ax ? b, ? is the type of constraint
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%
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% Output:
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% z - solution
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% mu - multipliers on the constraints
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% f - function evaluation at the solution
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% J - jacobian evaluation at the solution
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Big = 1e20;
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if (nargin < 1)
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error('one input arguments required for mcp(z)');
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end
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z = full(z(:));
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n = length(z);
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if (n == 0)
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error('empty model');
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end
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if (nargin < 2 | isempty(l))
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l = zeros(n,1);
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end
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if (nargin < 3 | isempty(u))
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u = Big*ones(n,1);
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end
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l = full(l(:)); u = full(u(:));
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if (length(l) ~= n | length(u) ~= n)
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error('Input arguments are of incompatible sizes');
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end
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l = max(l,-Big*ones(n,1));
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u = min(u,Big*ones(n,1));
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z = min(max(z,l),u);
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if (nargin < 4 | isempty(cpfj))
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cpfj = 'mcp_funjac';
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end
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m = 0;
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mu = [];
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l_p = [];
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u_p = [];
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if (nargin > 4)
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if (nargin < 6)
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error('Polyhedral constraints require A and b');
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end
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if (~issparse(A))
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A = sparse(A);
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end
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b = full(b(:));
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m = length(b);
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if (m > 0)
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[am, an] = size(A);
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if (am ~= m | an ~= n)
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error('Polyhedral constraints of incompatible sizes');
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end
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if (nargin < 7 | isempty(t))
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t = ones(m,1);
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end
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if (nargin < 8 | isempty(mu))
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mu = zeros(m,1);
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end
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t = full(t(:)); mu = full(mu(:));
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if (length(t) ~= m | length(mu) ~= m)
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error('Polyhedral input arguments are of incompatible sizes');
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end
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l_p = -Big*ones(m,1);
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u_p = Big*ones(m,1);
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idx = find(t > 0);
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if (length(idx) > 0)
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l_p(idx) = zeros(length(idx),1);
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end
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idx = find(t < 0);
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if (length(idx) > 0)
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u_p(idx) = zeros(length(idx),1);
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end
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mu = min(max(mu,l_p),u_p);
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else
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if (nargin >= 8 & ~isempty(mu))
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error('No polyhedral constraints -- multipliers set.');
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end
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if (nargin >= 7 & ~isempty(t))
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error('No polyhedral constraints -- equation types set.');
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end
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end
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else
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A = [];
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end
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% this is a fix, nnz may be bigger than this
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[f,J,domerr] = feval(cpfj,z+1e-5*ones(size(z))+1e-5*abs(z),1);
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if (domerr > 0)
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[f,J,domerr] = feval(cpfj,z,1);
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end
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if (domerr > 0)
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error([cpfj ' not defined at starting point']);
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end
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if ~issparse(J)
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error([cpfj ' must return a sparse Jacobian']);
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end
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nnzJ = nzmax(J);
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row = n + m;
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ele = nnzJ + 2*nzmax(A);
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init = [z; mu];
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low = [l; l_p];
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upp = [u; u_p];
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if m > 0
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global mcp_vifunc;
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global mcp_viconn;
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global mcp_viconm;
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global mcp_viconA;
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global mcp_viconb;
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mcp_vifunc = cpfj;
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mcp_viconn = n;
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mcp_viconm = m;
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mcp_viconA = A;
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mcp_viconb = b;
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[status, ttime, f, J] = mcppath(row, ele, init, low, upp, 'mcp_vifunjac');
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else
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[status, ttime, f, J] = mcppath(row, ele, init, low, upp, cpfj);
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end
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%if (status ~= 1)
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% status,
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% error('Path fails to solve problem');
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%end
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mu = [];
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z = init;
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if m > 0
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mu = init(n+1:n+m);
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z = init(1:n);
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J = J(1:n,1:n);
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f = f(1:n) + A'*mu;
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end
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return;
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Reference in New Issue