Revision 162, 0.9 kB
(checked in by smidl, 16 years ago)
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opravy a dokumentace
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1 | #include <estim/arx.h> |
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2 | #include <stat/libEF.h> |
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3 | using namespace itpp; |
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4 | |
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5 | //These lines are needed for use of cout and endl |
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6 | using std::cout; |
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7 | using std::endl; |
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8 | |
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9 | int main() { |
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10 | // Setup model |
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11 | vec th("0.8 -0.3 0.4 0.01"); |
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12 | int ord=th.length(); |
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13 | double sqr=1; |
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14 | |
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15 | //Test constructor |
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16 | mat V0 = 0.001*eye(ord+1); V0(0.0)*= 10; // |
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17 | double nu0 = ord+1; |
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18 | |
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19 | RV thr("{theta_and_r }"); |
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20 | ARX Ar(thr, V0, nu0); |
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21 | epdf& Ar_ep = Ar._epdf(); |
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22 | |
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23 | //Test estimation |
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24 | int ndat = 1000; |
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25 | int t,j; |
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26 | vec Yt(ndat); |
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27 | vec LL(ndat); |
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28 | Yt.set_subvector(0,randn(ord)); //initial values |
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29 | vec rgr(ord); |
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30 | |
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31 | cout << Ar_ep.mean()<<endl; |
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32 | for (t=ord; t<ndat; t++) { |
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33 | for(j=0;j<(ord);j++){rgr(j)=Yt(t-j-1);} |
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34 | Yt(t) = th*rgr + sqr * NorRNG(); |
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35 | |
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36 | vec Psi = concat(Yt(t), rgr); |
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37 | Ar.bayes(Psi); |
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38 | LL(t) = Ar._ll(); |
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39 | } |
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40 | cout << Ar_ep.mean()<<endl; |
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41 | |
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42 | // Test brute-froce structure estimation |
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43 | cout << Ar.structure_est(egiw(thr,V0,nu0)) <<endl; |
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44 | } |
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