void testTRobustEstimator3_columns_specific()
{
	const int N_OBSERVATIONS = 10;
	const int N_ATTRIBUTES = 3;
	Double_t data[N_ATTRIBUTES];
	TRobustEstimator rob(N_OBSERVATIONS, N_ATTRIBUTES);

	double s0 = 0;
	Double_t x1  =1;
	Double_t x2 = 3;
	Double_t x3 = 5;
	FILE *fp;
	fp = fopen("testTRobustEstimator3_columns_specific.txt", "w");
	for (int i = 1; i <= N_OBSERVATIONS; i++) {
		if (i%10 == 0) {
			data[0] = 100;
			data[1] = 0;
			data[2] = 0;
		}
		else {
			data[0] = x1;
			data[1] = x2;
			data[2] = x3;
			x1++;
			if (x1 == 4) x1 = 1;
			x2++;
			if (x2 == 6) x2 = 3;
			x3++;
			if (x3 == 8) x3 = 5;
		}
		rob.AddRow(data);
		s0 = s0 + data[0];
		fprintf(fp, "%f %f %f\n", data[0], data[1], data[2]);
		//fprintf(stderr, "%f %f %f\n", data[0], data[1], data[2]);
	}
	fclose(fp);
	double avg0 = s0 / N_OBSERVATIONS;
	fprintf(stderr, "--------------------> Mean value of attribute 0 = %f\n", avg0); // 11.8
	rob.Evaluate();
	for (int i = 0; i < N_ATTRIBUTES; i++) {
		fprintf(stderr, "Mean value of attribute %d = %f\n", i, rob.GetMean()[0][i]);
	}
	int Nobservations = rob.GetNumberObservations();
	fprintf(stderr, "Number of observations: %d\n", Nobservations);
	int Noutliers = rob.GetNOut();
	fprintf(stderr, "Number of Noutliers: %d (%.1f%%)\n", Noutliers, (double)Noutliers/(double)Nobservations*100);
	TArrayI OutliersIndexesArray = *(rob.GetOuliers()); //returns an array of outlier indexes
	int OutliersIndexesArraySize = OutliersIndexesArray.fN;
	//fprintf(stderr, "OutliersIndexesArraySize: %d\n", OutliersIndexesArraySize);
	for (int i=0; i<OutliersIndexesArraySize; i++) {
		int outlierIndx = OutliersIndexesArray[i];
		fprintf(stderr, "\tOutlier index: %d\n", outlierIndx);
	}
	rob.GetMean()->Print();
}