29 | | vec thu =vec_2 ( at,ct ); //Simulated system - zero for constant term |
30 | | vec Thy = concat ( thy, vec_1(sig) ); //Full parameter |
31 | | vec Thu = concat ( thu, vec_1(sig) ); //Full parameter |
| 34 | vec thz =vec_2 ( at,ct ); //Simulated system - zero for constant term |
| 35 | vec Thy = concat ( thy, vec_1(rt) ); //Full parameter |
| 36 | vec Thz = concat ( thz, vec_1(rt) ); //Full parameter |
36 | | ARX P1 ( concat ( a, concat(b,r) ), V0, -1 ); |
37 | | ARX P2 ( concat ( a, concat(c,r) ), V0, -1 ); |
| 41 | ARX P1 ( concat ( ab,r ), V0, -1 ); |
| 42 | ARX P2 ( concat ( ac,r ), V0, -1 ); |
44 | | dirfilelog L ( "exp/merg_2a",ndat ); |
45 | | int Li_Data = L.add ( RV ( "{Y U1 U2 }" ), "" ); |
46 | | int Li_LL = L.add ( RV ( "{G M }" ), "LL" ); |
47 | | int Li_P1m = L.add ( RV ( "{a b r }" ), "P1" ); |
48 | | int Li_P2m = L.add ( RV ( "{a c r }" ), "P2" ); |
| 49 | dirfilelog L ( "exp/merg_2a",3 ); |
| 50 | int Li_Data = L.add ( RV ( "{U Y Z }" ), "" ); |
| 51 | // int Li_LL = L.add ( RV ( "{P1 P2 M1 M2 }" ), "LL" ); |
| 52 | int Li_P1m = L.add ( concat ( ab,r ), "P1m" ); |
| 53 | int Li_P2m = L.add ( concat ( ac,r ), "P2m" ); |
| 54 | int Li_Mm = L.add ( concat ( ab,concat(r,c) ), "Mm" ); |
64 | | rgrg ( 0 ) = pow ( sin ( ( t/40.0 ) *pi ),3 ); |
65 | | rgrg ( 1 ) = pow ( cos ( ( t/40.0 +0.1 ) *pi ),3 ); |
66 | | |
67 | | Yt ( t ) = thg*rgrg + sqr * NorRNG(); |
| 76 | Ut ( t ) = pow ( sin ( ( t/40.0 ) *pi ),3 ); |
| 77 | rgru(0) = Ut(t); rgru(1) = Ut(t-1); |
| 78 | Yt ( t ) = thy*rgru + rt * NorRNG(); |
| 79 | rgry(0) = Yt(t); rgry(1) = Yt(t-1); |
| 80 | Zt ( t ) = thz*rgry + rt * NorRNG(); |
70 | | P1.bayes ( concat ( Yt ( t ),vec_1 ( rgrg ( 0 ) ) ) ); |
71 | | P2.bayes ( concat ( Yt ( t ),vec_1 ( rgrg ( 1 ) ) ) ); |
72 | | PG.bayes ( concat ( Yt ( t ),rgrg ) ); |
73 | | |
74 | | |
75 | | // crippling PGk by substituting zeros. |
76 | | /* ldmat &Vk=const_cast<egiw*>(PGk._e())->_V(); //PG ldmat does not like 0! |
77 | | mat fVk=PG._e()->_V().to_mat(); |
78 | | fVk(1,2) = 0.0; |
79 | | fVk(2,1) = 0.0; |
80 | | Vk = ldmat(fVk); |
81 | | */ //PGk is now krippled |
| 83 | P1.bayes ( concat ( Yt ( t ),rgru ) ); |
| 84 | P2.bayes ( concat ( Zt ( t ),rgry ) ); |
96 | | // LLs ( 0 ) = P1._e()->evalpdflog ( get_vec(Th, "1 2") ); |
97 | | // LLs ( 1 ) = P2._e()->evalpdflog ( get_vec(Th, "3 2") ); |
98 | | LLs ( 0 ) = PG._e()->evalpdflog ( Th ); |
99 | | LLs ( 1 ) = M._Mix().logpred ( concat ( Thj, vec_1 ( 1.0 ) ) ); |
100 | | // LLs ( 3 ) = M2._Mix().logpred ( concat(Thj, vec_1(1.0)) ); |
101 | | L.logit ( Li_LL, LLs ); //log-normal |
102 | | |
104 | | L.logit ( Li_Data, vec_3 ( Yt ( t ), rgrg ( 0 ), rgrg ( 1 ) ) ); |
105 | | L.logit ( Li_P1m, P1._e()->mean() ); |
106 | | L.logit ( Li_P2m, P2._e()->mean() ); |
107 | | L.logit ( Li_Gm, PG._e()->mean() ); |
108 | | L.logit ( Li_Mm, M.mean() ); |
109 | | |
| 99 | L.logit(Li_Data, vec_3(Ut(t), Yt(t), Zt(t))); |
| 100 | L.logit(Li_P1m, P1._e()->mean()); |
| 101 | L.logit(Li_P2m, P2._e()->mean()); |
| 102 | L.logit(Li_Mm, M.mean()); |