[765] | 1 | % name random variables |
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| 2 | y = RV({'y'},1); |
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| 3 | u1 = RV({'u1'},1); |
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| 4 | u2 = RV({'u2'},1); |
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| 5 | |
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| 6 | % create f(y_t| y_{t-3}, u_{t-1}) |
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| 7 | fy.class = 'mlnorm<ldmat>'; |
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| 8 | fy.rv = y; |
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| 9 | fy.rvc = RVtimes([y,u1,u2], [-3, 0, 0]); |
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| 10 | fy.A = [0.5, -0.9, 0.9]; |
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| 11 | fy.const = 0; |
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| 12 | fy.R = 1e-2; |
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| 13 | |
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| 14 | DS.class = 'PdfDS'; |
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| 15 | DS.pdf = fy; |
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| 16 | |
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| 17 | % create ARX estimator |
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| 18 | A1.class = 'ARX'; |
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| 19 | A1.rv = y; |
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| 20 | A1.rgr = RVtimes([y,u1],[-3,0]) ; % correct structure is {y,y} |
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| 21 | A1.options ='logbounds,logll'; |
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| 22 | A1.frg = 0.95; |
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| 23 | |
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| 24 | A2=A1; |
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| 25 | A2.rgr = RVtimes([y,u2],[-3,0]) ; % correct structure is {y,y} |
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| 26 | |
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| 27 | |
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| 28 | C1.class = 'LQG_ARX'; |
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| 29 | C1.ARX = A1; |
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| 30 | C1.Qu = 0.1*eye(1); |
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| 31 | C1.Qy = 1*eye(1); |
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| 32 | C1.yreq = 1; |
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[774] | 33 | C1.horizon = 5; |
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[765] | 34 | |
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| 35 | C2=C1; |
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| 36 | C2.ARX = A2; |
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| 37 | |
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| 38 | P1.class = 'ARXAgent'; |
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| 39 | P1.name = 'P1'; |
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| 40 | P1.lqg_arx = C1; |
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| 41 | P1.lqg_arx.class = 'LQG_ARX'; |
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| 42 | P1.merger.class = 'merger_mix'; |
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| 43 | P1.merger.method = 'geometric'; |
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[774] | 44 | %P1.merger.dbg_file = 'mp.it'; |
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| 45 | P1.merger.ncoms = 20; |
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| 46 | P1.neighbours = {};%{'P2'}; |
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[765] | 47 | |
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| 48 | P2=P1; |
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| 49 | P2.name = 'P2'; |
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| 50 | P2.lqg_arx = C2; |
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| 51 | P2.neighbours = {}; |
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| 52 | |
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[774] | 53 | exper.Ndat = 10; |
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| 54 | exper.burnin = 3; |
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[765] | 55 | exper.burn_pdf.class = 'enorm<ldmat>'; |
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| 56 | exper.burn_pdf.mu = [0;0]; |
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| 57 | exper.burn_pdf.R = 0.01*eye(2); |
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| 58 | |
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| 59 | |
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[774] | 60 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% MONTE CARLO %%%%%%%%%%%%%%%%%%% |
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[765] | 61 | |
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[774] | 62 | Ntrials = 100; |
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| 63 | loss_non_coop = zeros(1,Ntrials); |
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| 64 | for i=1:Ntrials |
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| 65 | M= arena(DS,{P1,P2},exper); |
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[765] | 66 | |
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[774] | 67 | loss_non_coop(i) = M.DS_y'*C1.Qy*M.DS_y + M.DS_u1'*C1.Qu*M.DS_u1 + M.DS_u2'*C1.Qu*M.DS_u2; |
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| 68 | end |
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| 69 | mean(loss_non_coop) |
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