推 abidog:洗文章數喔 06/01 16:19
=================================開始複製======================================
#include <C:\devcpp\all.h>
int main()
{
long int i, j;
srand((unsigned)time(NULL));
cout.setf(ios::fixed); cout.precision(10);
// $$$$$$$$ Start your program here $$$$$$$$$$$$$$$$$$$$$
Matrix Y;
Y.read_from_file("c:\\devcpp\\twoway.dat",1);
Y.print(1);
Two_way_class(4,6,1).print(0);
Matrix C = Two_way_class(4,6,1);
Matrix X = J_Mat(Y.row(),1);
X.print(0);
X.append_column(gen_dummy(C.col(1)));
X.print(0);
Matrix SST, SSR_f, SSR_r, SSE_f, SSE_r;
Part_SS_X_full(Y,X,SST,SSR_r,SSE_r);
cout << "Reduced Model SS = " << endl;
SSR_r.print(3);
SSE_r.print(3);
SST.print(3);
X.append_column(gen_dummy(C.col(0)));
Part_SS_X_full(Y,X,SST,SSR_f,SSE_f);
cout << " Full Model SS = " << endl;
SSR_f.print(3);
SSE_f.print(3);
SST.print(3);
double F = ((SSE_r-SSE_f)/3.0)/
(SSE_f/15.0);
cout << "paramatric approach under normal assumption" << endl;
cout << "F_value = " << F << endl;
cout << "P_value = " << F_r_tailed_prob(F,3,15) << endl;
Partial_F_test(Y,X,6,8);
double SSE0 = SSE_f;
Univar SSE_Monte_Carlo;
for(i=0; i <1000; i++)
{ X.randomize_row(6,8);
Part_SS_X_non_full(Y,X,SST,SSR_f,SSE_f);
SSE_Monte_Carlo.push_back(SSE_f);
}
SSE_Monte_Carlo.freq_dist(-2);
cout.precision(4);
cout << "Monte_Carlo Randomization Test P_value = ";
cout << SSE_Monte_Carlo.emp_CDF(SSE0) << endl;
/* srand(66);
Matrix K(6,4);
K.bin_ran(100,0.5);
K.print(0);
K.randomize_row(1,2).print(0);
*/
// $$$$$$$ End of your program $$$$$$$$$$$$$$$$$$$$$$$$$
cin.get();
return 0;
====================================複製結束===================================
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