| 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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| 18 | fz.const = 0.2; | 
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| 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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| 36 | A1.log_level ='logfull,logevidence'; | 
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| 37 | A1.rv_param = RV({'a','b','c','r'}); | 
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| 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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| 43 | A2.rv_param = RV({'a','b','c','r'}); | 
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| 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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| 56 | %Merger.dbg_file = 'm.it'; | 
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| 57 |  | 
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| 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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| 62 | support.class='discrete_support'; | 
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| 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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| 65 |  | 
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| 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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| 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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| 81 | MG_mean = zeros(4,ndat); | 
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| 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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| 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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| 90 | [res,ftilde] = merger({f1,f2},support,Merger); | 
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| 91 |  | 
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| 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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| 113 | plot(A1_mean',':'); | 
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| 114 | hold on; | 
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| 115 | plot(A2_mean','--'); | 
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| 116 | plot(MG_mean'); | 
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