wolffd@0: function bnet = mk_mildew_dbn()
wolffd@0: 
wolffd@0: % DBN for foreacasting the gross yield of wheat based on climatic data,
wolffd@0: % observations of leaf area index (LAI) and extension of mildew,
wolffd@0: % and knowledge of amount of fungicides used and time of usage.
wolffd@0: % From Kjaerulff '95.
wolffd@0: 
wolffd@0: Fungi=1; Mildew=2; LAI=3; Precip=4; Temp=5; Micro=6; Solar=7; Photo=8; Dry=9;
wolffd@0: n = 9;
wolffd@0: intra = zeros(n,n);
wolffd@0: intra(Mildew, LAI)=1;
wolffd@0: intra(LAI,[Micro Photo])=1;
wolffd@0: intra(Precip,Micro)=1;
wolffd@0: intra(Temp,[Micro Photo])=1;
wolffd@0: intra(Solar,Photo)=1;
wolffd@0: intra(Photo,Dry)=1;
wolffd@0: 
wolffd@0: inter = zeros(n,n);
wolffd@0: inter(Fungi,Mildew)=1;
wolffd@0: inter(Mildew,Mildew)=1;
wolffd@0: inter(LAI,LAI)=1;
wolffd@0: inter(Micro,Mildew)=1;
wolffd@0: inter(Dry,Dry)=1;
wolffd@0: 
wolffd@0: ns = 2*ones(1,n);
wolffd@0: bnet = mk_dbn(intra, inter, ns, 'observed', [Photo]);
wolffd@0: 
wolffd@0: for e=1:max(bnet.equiv_class(:))
wolffd@0:   i = bnet.rep_of_eclass(e);
wolffd@0:   bnet.CPD{e} = tabular_CPD(bnet,i);
wolffd@0: end