1 | #include <itpp/itbase.h> |
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2 | #include <stat/libEF.h> |
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3 | |
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4 | using namespace itpp; |
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5 | |
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6 | //These lines are needed for use of cout and endl |
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7 | using std::cout; |
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8 | using std::endl; |
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9 | |
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10 | void disp(const vec &tmu, const mat &tR,const mat &Smp){ |
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11 | int N = Smp.cols(); |
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12 | vec Emu = Smp*ones(N) /N ; |
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13 | mat Er = (Smp*Smp.transpose())/N - outer_product(Emu,Emu); |
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14 | cout << "True mu:" << tmu <<endl; |
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15 | cout << "Emp mu:" << Emu <<endl; |
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16 | |
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17 | cout << "True R:" << tR <<endl; |
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18 | cout << "Emp R:" << Er <<endl; |
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19 | } |
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20 | |
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21 | int main() { |
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22 | |
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23 | RNG_randomize(); |
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24 | |
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25 | RV rv("1","{x }","2","0"); |
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26 | int N = 10000; //number of samples |
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27 | vec mu0 = "1.5 1.7"; |
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28 | mat V0("1.2 0.3; 0.3 5"); |
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29 | ldmat R = ldmat(V0); |
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30 | |
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31 | cout << "====== ENorm ====== " <<endl; |
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32 | enorm<ldmat> eN(rv); |
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33 | eN.set_parameters(mu0,R); |
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34 | mat Smp = eN.sample(N); |
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35 | |
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36 | disp(mu0,R.to_mat(),Smp); |
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37 | |
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38 | cout << "====== MlNorm ====== " <<endl; |
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39 | mat I = eye(2); |
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40 | vec lik(N); |
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41 | mlnorm<ldmat> ML(rv,rv); |
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42 | ML.set_parameters(I,R); |
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43 | Smp = ML.samplecond(mu0,lik,N); |
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44 | |
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45 | disp(mu0,R.to_mat(),Smp); |
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46 | |
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47 | cout << "====== EGamma ====== " <<endl; |
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48 | vec a = "100000,10000"; |
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49 | vec b = a/10.0; |
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50 | egamma eG(rv); |
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51 | eG.set_parameters(a,b); |
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52 | |
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53 | Smp = eG.sample(N); |
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54 | |
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55 | vec g_mu = elem_div(a,b); |
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56 | vec g_var = elem_div(a,pow(b,2.0)); |
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57 | disp(g_mu,diag(g_var),Smp); |
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58 | |
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59 | cout << "====== MGamma ====== " <<endl; |
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60 | mgamma mG(rv,rv); |
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61 | double k = 10.0; |
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62 | mG.set_parameters(k); |
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63 | |
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64 | Smp=mG.samplecond(mu0,lik,N); |
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65 | disp(mu0,pow(mu0,2.0)/k,Smp); |
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66 | |
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67 | //Exit program: |
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68 | return 0; |
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69 | |
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70 | } |
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