[759] | 1 | % name random variables |
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| 2 | y = RV({'y'},1); |
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| 3 | z = RV({'z'},1); |
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| 4 | u = RV({'u'},1); |
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| 5 | |
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| 6 | % create f(y_t| z_{t-1}, z_{t-2}) |
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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([z,z], [0, -1]); |
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| 10 | fy.A = [1.8, -0.9]; |
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| 11 | fy.const = 0.2; |
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| 12 | fy.R = 1e-2; |
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| 13 | |
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| 14 | fz.class = 'mlnorm<ldmat>'; |
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| 15 | fz.rv = z; |
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| 16 | fz.rvc = RVtimes([u,u], [0, -1]); |
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| 17 | fz.A = [1.8, -0.9]; |
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[761] | 18 | fz.const = 0.2; |
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[759] | 19 | fz.R = 1e-2; |
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| 20 | |
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| 21 | fu.class = 'enorm<ldmat>'; |
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| 22 | fu.rv = u; |
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| 23 | fu.mu = [0]; |
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| 24 | fu.R = 0.001; |
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| 25 | |
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| 26 | f.class = 'mprod'; |
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| 27 | f.pdfs = {fy,fz,fu}; |
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| 28 | |
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| 29 | DS.class = 'PdfDS'; |
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| 30 | DS.pdf = f; |
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| 31 | |
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| 32 | % create ARX estimator |
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| 33 | A1.class = 'ARX'; |
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| 34 | A1.rv = y; |
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| 35 | A1.rgr = RVtimes([z,z],[0,-1]) ; % correct structure is {y,y} |
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[871] | 36 | A1.log_level ='logfull,logevidence'; |
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[761] | 37 | A1.rv_param = RV({'a','b','c','r'}); |
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[759] | 38 | A1.frg = 0.95; |
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| 39 | A1.constant = 1; |
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| 40 | |
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| 41 | A2=A1; |
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| 42 | A2.rv = z; |
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[761] | 43 | A2.rv_param = RV({'a','b','c','r'}); |
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[759] | 44 | A2.rgr = RVtimes([u,u],[0,-1]) ; % correct structure is {y,y} |
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| 45 | |
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| 46 | [M,Set]=estimator(DS,{A1,A2},struct('ndat',100)); |
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| 47 | |
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| 48 | %% post-merging |
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| 49 | |
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| 50 | Merger.class='merger_mix'; |
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| 51 | Merger.method='lognormal'; |
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| 52 | Merger.beta=1.2; |
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| 53 | Merger.ncoms=20; |
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| 54 | Merger.stop_niter=10; |
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| 55 | Merger.effss_coef=0.9; |
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[761] | 56 | %Merger.dbg_file = 'm.it'; |
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[759] | 57 | |
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[761] | 58 | M2.class = 'merger_base'; |
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| 59 | M2.method='lognormal'; |
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| 60 | M2.beta=1.2; |
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| 61 | |
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[759] | 62 | support.class='discrete_support'; |
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[761] | 63 | support.epdf= struct('class','enorm<ldmat>','mu',[2,-1,0,0.1],'R',eye(4)); |
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| 64 | support.npoints=[300]; |
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[759] | 65 | |
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[761] | 66 | support2.class='rectangular_support'; |
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| 67 | support2.ranges= {[0,5],[-2,2],[-2,2],[0.001,3]}; |
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| 68 | support2.gridsizes = [10,10,10,10]; |
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[759] | 69 | |
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| 70 | |
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| 71 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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| 72 | % plot results |
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| 73 | ndat = size(M.DS_u,1); |
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| 74 | |
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| 75 | true_theta1 = [fy.A fy.const]; |
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| 76 | true_theta2 = [fz.A fy.const]; |
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| 77 | true_R = fy.R; |
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| 78 | |
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| 79 | A1_mean = zeros(4,ndat); |
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| 80 | A2_mean = zeros(4,ndat); |
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[761] | 81 | MG_mean = zeros(4,ndat); |
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[759] | 82 | |
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| 83 | for t=1:ndat |
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| 84 | f1=Set.Est0_apost{t}; |
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| 85 | f2=Set.Est1_apost{t}; |
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[761] | 86 | if t>5 |
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| 87 | % support.epdf = f1; |
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| 88 | end |
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| 89 | |
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[759] | 90 | [res,ftilde] = merger({f1,f2},support,Merger); |
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[761] | 91 | |
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[759] | 92 | A1_mean(:,t) = epdf_mean(f1); |
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| 93 | A2_mean(:,t) = epdf_mean(f2); |
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| 94 | MG_mean(:,t) = epdf_mean(ftilde); |
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| 95 | end; |
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| 96 | |
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| 97 | |
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| 98 | figure(1); |
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| 99 | subplot(3,1,1); |
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| 100 | plot(M.DS_y); |
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| 101 | title('y'); |
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| 102 | |
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| 103 | subplot(3,1,2); |
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| 104 | plot(M.DS_z); |
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| 105 | title('z') |
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| 106 | |
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| 107 | subplot(3,1,2); |
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| 108 | plot(M.DS_u); |
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| 109 | title('u') |
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| 110 | |
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| 111 | |
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| 112 | figure(2) |
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[761] | 113 | plot(A1_mean',':'); |
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| 114 | hold on; |
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| 115 | plot(A2_mean','--'); |
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[759] | 116 | plot(MG_mean'); |
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