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Timestamp:
10/15/09 00:10:19 (15 years ago)
Author:
smidl
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doc

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  • applications/dual/experiment/itermc.m

    r650 r661  
    33c.sigma = 0.1; 
    44c.ndat = 50; 
    5  
    65yr = 1; 
    76 
     
    1413C2.class='ce_ctrl'; 
    1514C2.yr   = yr; 
    16 C2.b0   = -0.; 
     15C2.b0   = 0; 
    1716C2.P0   = 1; 
    18  
    19 c.controller = C1; 
    20 M1=iterativemc(c); 
    21  
    22 loss_exact = sum((M1.y-yr*ones(size(M1.y))).^2) 
    23 loss_theory = c.ndat*c.sigma^2 
    24  
    25 c.controller = C2; 
    26 M2=iterativemc(c); 
    27  
    28 loss_ce = sum((M2.y-yr*ones(size(M2.y))).^2) 
    2917 
    3018% monte carlo study 
    3119n=100; 
    3220losses=zeros(10,1); 
    33 c.controller = C1; 
    3421seeds=32000*rand(1,n); 
    3522for i=1:n 
     23    c.b = randn(); 
    3624    c.seed = seeds(i);  
     25    c.controller = C1; 
    3726    Mmc=iterativemc(c); 
    3827    losses(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2); 
     28     
     29    c.controller = C2; 
     30    Mmc=iterativemc(c); 
     31    losses2(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2); 
    3932end 
    40 [min(losses) mean(losses) max(losses)] 
    41      
     33[min(losses) median(losses) max(losses)] 
     34[min(losses2) median(losses2) max(losses2)] 
     35