/src/main/java/net/finmath/marketdata/model/curves/locallinearregression/CurveEstimation.java
partitionAsVector.getRange( 0, partitionAsVector.length-1) .ones( ) .add( independentValues[i]).mul( kernelValues).add( partitionIncrements.getRange( 1, partitionIncrements.length).mul( kernelSum.getRange( 1, kernelSum.length) ) ) ) ;
partitionAsVector.getRange ( 0, partitionAsVector.length-1 ) .neg ( ) .add ( independentValues[i] ) .mul ( kernelValues ) .add ( partitionIncrements.getRange ( 1, partitionIncrements.length ) .mul ( kernelSum.getRange ( 1, kernelSum.length ) ) ) ) ;
.mul(partitionAsVector.getRange(0,partitionAsVector.length-1).neg().add(independentValues[i])) .mul(kernelValues).add( partitionIncrements.getRange(1,partitionAsVector.length) .mul(partitionIncrements.getRange(1,partitionAsVector.length) .mul(kernelSum.getRange(1, kernelSum.length))))); MSubMatrixSum=MSubMatrixSum.add( <extra_id_0> } final DoubleMatrix partitionIncrementMatrix= new DoubleMatrix(partition.getLength()-1,partition.getLength()-1); final DoubleMatrix matrixDefine= DoubleMatrix.ones(partition.getLength()-1); for(int m=0;m<matrixDefine.length-1;m++) { matrixDefine.put(m, 0); partitionIncrementMatrix.putColumn(m, matrixDefine.mul(partitionIncrements.get(m+1)));