gen_random_start.m

The BNL toolbox is a set of Matlab functions for defining and estimating the parameters of a Bayesi

function [parms,restparms]=gen_random_start(design,parents,equiv_class,param_equiv_class,gausskwadnodes,link)

parms=cell(max(param_equiv_class),1);
for i=1:max(param_equiv_class);
    node_nr=find(param_equiv_class==i,1);
    if ~mysubset(node_nr, gausskwadnodes.nodenrs) parms{i}=rand(size(design{equiv_class(node_nr)},2),1)/4-.125;
        if ~isempty(myintersect(gausskwadnodes.nodenrs,parents{node_nr}))
            parms{i}(1)=abs(parms{i}(1));%stdev of guasskwad nodes must be positive
        end
        restparms{i}=zeros(size(design{equiv_class(node_nr)},2),1);
    else
         f=find(gausskwadnodes.nodenrs==node_nr);
         [x,w]=herzo(gausskwadnodes.nodesizes(f));
         if link{i}=='multinomial'
            parms{i}=multinom_logit(w')';
         elseif link{i}=='cumulative'
            parms{i}=cum_logit(w')';
         elseif link{i}=='adjacent'
            parms{i}=adj_logit(w')';
         else error('no valid link fnction for gausskwad nodes');
         end
         restparms{i}=ones(size(design{equiv_class(node_nr)},2),1);
    end
end