int main(int argc, char* argv[]) {
LogisticRegression lr;
LogisticRegressionScoreTest lrst;
LogisticRegressionPermutationTest lrpt;
Vector y;
Matrix x;
Matrix cov;
LoadVector("input.y", y);
LoadMatrix("input.x", x);
LoadMatrix("input.cov", cov);
Matrix xall;
xall = x;
xall.StackRight(cov); // 1 + x + cov
if (lr.FitLogisticModel(xall, y, 100) == false) {
fprintf(stderr, "Fitting failed!\n");
return -1;
}
Vector& beta = lr.GetCovEst();
Matrix& v = lr.GetCovB();
Vector& pWald = lr.GetAsyPvalue();
fprintf(stdout, "wald_beta\t");
Print(beta);
fputc('\n', stdout);
fprintf(stdout, "wald_vcov\t");
Print(v);
fputc('\n', stdout);
fprintf(stdout, "wald_p\t");
Print(pWald[1]);
fputc('\n', stdout);
if (lrpt.FitLogisticModelCov(xall, 1, y, 2000, -1) == false) {
fprintf(stderr, "Fitting failed!\n");
return -1;
}
fprintf(stdout, "permutation_p\t");
double permu_p = lrpt.getPvalue();
Print(permu_p);
fputc('\n', stdout);
if (lrst.FitLogisticModel(xall, y, 1, 100) == false) {
fprintf(stderr, "Fitting failed!\n");
return -1;
}
fprintf(stdout, "score_p\t");
double score_p = lrst.GetPvalue();
Print(score_p);
fputc('\n', stdout);
return 0;
};
int main(int argc, char *argv[])
{
time_t now = time(0);
printf("chisq p = 0.05 cutoff = %f",chidist(3.84, 1.0));
printf("Start analysis at %s \n", ctime(&now));
/*
Matrix a(2,2);
a[0][0] = 1.0;
a[1][1] = 1.0;
a[0][1] = a[1][0] = 0.5;
SVD svd;
svd.InvertInPlace(a);
for (int i = 0; i < a.rows; i ++) {
for (int j = 0; j < a.cols; j ++) {
std::cout << "a[" << i << "]" << "[" << j << "]" << a[i][j] << "\t";
}
std::cout << "\n";
}
return 0;
*/
Matrix X;
String Xinput = "ExampleX.test";
Vector Y;
String Yinput = "ExampleY.test";
if (loadMatrix(X,Xinput) || loadVector(Y, Yinput)) {
fprintf(stderr, "Data loading problem!\n");
exit(1);
}
LogisticRegression lr;
if (lr.FitLogisticModel(X, Y, 30) ) {
printf("fit all right!\n");
} else {
printf("fit failed\n");
}
now = time(0);
printf("Finsihed analysis at %s \n", ctime(&now));
LogisticRegressionScoreTest lrst;
int Xcol = 1;
lrst.FitLogisticModel(X,Y,Xcol,30);
printf("score p-value is: %lf \n", lrst.getPvalue());
Vector& pvalue = lr.GetAsyPvalue();
printf("wald p-value is: %lf \n", pvalue[Xcol]);
return 0;
}