本文整理汇总了Java中org.apache.commons.math3.linear.RealMatrix.scalarMultiply方法的典型用法代码示例。如果您正苦于以下问题：Java RealMatrix.scalarMultiply方法的具体用法？Java RealMatrix.scalarMultiply怎么用？Java RealMatrix.scalarMultiply使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.commons.math3.linear.RealMatrix的用法示例。
在下文中一共展示了RealMatrix.scalarMultiply方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: main
import org.apache.commons.math3.linear.RealMatrix; //导入方法依赖的package包/类
public static void main(String[] args) {
// test wishart
double[][] s = {{2.0,1.0,0.0},{1.0,2.0,1.0},{0.0,1.0,2.0}};
RealMatrix S = new Array2DRowRealMatrix(s);
Cholesky C = new Cholesky(S);
double df = 2.4;
RealMatrix sum = new Array2DRowRealMatrix(3,3);
for (int i=0; i<100000; i++) {
RealMatrix sample = generator.nextWishart(df, C);
sum = sum.add(sample);
}
sum = sum.scalarMultiply(1.0/100000.0);
System.out.println(sum.getRowVector(0));
System.out.println(sum.getRowVector(1));
System.out.println(sum.getRowVector(2));
}
示例2: computeBeta
import org.apache.commons.math3.linear.RealMatrix; //导入方法依赖的package包/类
/**
*
* @param y the response vector
* @param x the design matrix
*/
private RealMatrix computeBeta(RealVector y, RealMatrix x) {
if (solver == Solver.QR) {
return computeBetaQR(y, x);
} else {
final int n = x.getRowDimension();
final int p = x.getColumnDimension();
final int offset = hasIntercept() ? 1 : 0;
final RealMatrix xT = x.transpose();
final RealMatrix xTxInv = new LUDecomposition(xT.multiply(x)).getSolver().getInverse();
final RealVector betaVector = xTxInv.multiply(xT).operate(y);
final RealVector residuals = y.subtract(x.operate(betaVector));
this.rss = residuals.dotProduct(residuals);
this.errorVariance = rss / (n - p);
this.stdError = Math.sqrt(errorVariance);
this.residuals = createResidualsFrame(residuals);
final RealMatrix covMatrix = xTxInv.scalarMultiply(errorVariance);
final RealMatrix result = new Array2DRowRealMatrix(p, 2);
if (hasIntercept()) {
result.setEntry(0, 0, betaVector.getEntry(0)); //Intercept coefficient
result.setEntry(0, 1, covMatrix.getEntry(0, 0)); //Intercept variance
}
for (int i = 0; i < getRegressors().size(); i++) {
final int index = i + offset;
final double variance = covMatrix.getEntry(index, index);
result.setEntry(index, 1, variance);
result.setEntry(index, 0, betaVector.getEntry(index));
}
return result;
}
}