| Package | Description |
|---|---|
| com.opengamma.strata.math.impl.interpolation | |
| com.opengamma.strata.math.impl.regression |
| Modifier and Type | Method and Description |
|---|---|
LeastSquaresRegressionResult |
PolynomialsLeastSquaresFitter.regress(double[] xData,
double[] yData,
int degree)
Given a set of data (X_i, Y_i) and degrees of a polynomial, determines optimal coefficients of the polynomial.
|
| Modifier and Type | Class and Description |
|---|---|
class |
NamedVariableLeastSquaresRegressionResult |
class |
WeightedLeastSquaresRegressionResult |
| Modifier and Type | Method and Description |
|---|---|
LeastSquaresRegressionResult |
NamedVariableLeastSquaresRegressionResult.getResult() |
LeastSquaresRegressionResult |
WeightedLeastSquaresRegression.regress(double[][] x,
double[][] weights,
double[] y,
boolean useIntercept) |
LeastSquaresRegressionResult |
OrdinaryLeastSquaresRegression.regress(double[][] x,
double[][] weights,
double[] y,
boolean useIntercept) |
abstract LeastSquaresRegressionResult |
LeastSquaresRegression.regress(double[][] x,
double[][] weights,
double[] y,
boolean useIntercept) |
LeastSquaresRegressionResult |
GeneralizedLeastSquaresRegression.regress(double[][] x,
double[][] weights,
double[] y,
boolean useIntercept) |
LeastSquaresRegressionResult |
OrdinaryLeastSquaresRegression.regress(double[][] x,
double[] y,
boolean useIntercept) |
LeastSquaresRegressionResult |
WeightedLeastSquaresRegression.regress(double[][] x,
double[] weights,
double[] y,
boolean useIntercept) |
| Constructor and Description |
|---|
LeastSquaresRegressionResult(LeastSquaresRegressionResult result) |
NamedVariableLeastSquaresRegressionResult(List<String> independentVariableNames,
LeastSquaresRegressionResult result) |
WeightedLeastSquaresRegressionResult(LeastSquaresRegressionResult result) |
Copyright 2009-Present by OpenGamma Inc. and individual contributors
Apache v2 licensed
Additional documentation can be found at strata.opengamma.io.