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function [nodes,weights,nnodes] = setup_integration_nodes(EpOptions,pfm)
if EpOptions.stochastic.order
% Compute weights and nodes for the stochastic version of the extended path.
switch EpOptions.stochastic.IntegrationAlgorithm
case 'Tensor-Gaussian-Quadrature'
% Get the nodes and weights from a univariate Gauss-Hermite quadrature.
[nodes0,weights0] = gauss_hermite_weights_and_nodes(EpOptions.stochastic.quadrature.nodes);
% Replicate the univariate nodes for each innovation and dates, and, if needed, correlate them.
nodes0 = repmat(nodes0,1,pfm.number_of_shocks*pfm.stochastic_order)*kron(eye(pfm.stochastic_order),pfm.Omega);
% Put the nodes and weights in cells
for i=1:pfm.number_of_shocks
rr(i) = {nodes0(:,i)};
ww(i) = {weights0};
end
% Build the tensorial grid
nodes = cartesian_product_of_sets(rr{:});
weights = prod(cartesian_product_of_sets(ww{:}),2);
nnodes = length(weights);
case 'Stroud-Cubature-3'
[nodes,weights] = cubature_with_gaussian_weight(pfm.number_of_shocks*pfm.stochastic_order,3,'Stroud')
nodes = kron(eye(pfm.stochastic_order),transpose(pfm.Omega))*nodes;
weights = weights;
nnodes = length(weights);
case 'Stroud-Cubature-5'
[nodes,weights] = cubature_with_gaussian_weight(pfm.number_of_shocks*pfm.stochastic_order,5,'Stroud')
nodes = kron(eye(pfm.stochastic_order),transpose(pfm.Omega))*nodes;
weights = weights;
nnodes = length(weights);
case 'Unscented'
p = pfm.number_of_shocks;
k = 3;%EpOptions.ut.k;
C = sqrt(pfm.number_of_shocks + k)*pfm.Omega';
nodes = [zeros(1,p); -C; C];
weights = [k/(p+k); (1/(2*(p+k)))*ones(2*p,1)];
nnodes = 2*p+1;
otherwise
error('Stochastic extended path:: Unknown integration algorithm!')
end
end
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