MultipleLinearRegression (Hipparchus 1.4 API)

All Known Implementing Classes:

AbstractMultipleLinearRegression, GLSMultipleLinearRegression, OLSMultipleLinearRegression
```
public interface MultipleLinearRegression
```
The multiple linear regression can be represented in matrix-notation.
```
  y=X*b+u
 
```
where y is an n-vector regressand, X is a [n,k] matrix whose k columns are called regressors, b is k-vector of regression parameters and u is an n-vector of error terms or residuals. The notation is quite standard in literature, cf eg Davidson and MacKinnon, Econometrics Theory and Methods, 2004.

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`double`	`estimateRegressandVariance()`	Returns the variance of the regressand, ie Var(y).
`double[]`	`estimateRegressionParameters()`	Estimates the regression parameters b.
`double[]`	`estimateRegressionParametersStandardErrors()`	Returns the standard errors of the regression parameters.
`double[][]`	`estimateRegressionParametersVariance()`	Estimates the variance of the regression parameters, ie Var(b).
`double[]`	`estimateResiduals()`	Estimates the residuals, ie u = y - X*b.

- Method Detail
  - estimateRegressionParameters
```
double[] estimateRegressionParameters()
```
    Estimates the regression parameters b.
    
    Returns:
    
    The [k,1] array representing b
  - estimateRegressionParametersVariance
```
double[][] estimateRegressionParametersVariance()
```
    Estimates the variance of the regression parameters, ie Var(b).
    
    Returns:
    
    The [k,k] array representing the variance of b
  - estimateResiduals
```
double[] estimateResiduals()
```
    Estimates the residuals, ie u = y - X*b.
    
    Returns:
    
    The [n,1] array representing the residuals
  - estimateRegressandVariance
```
double estimateRegressandVariance()
```
    Returns the variance of the regressand, ie Var(y).
    
    Returns:
    
    The double representing the variance of y
  - estimateRegressionParametersStandardErrors
```
double[] estimateRegressionParametersStandardErrors()
```
    Returns the standard errors of the regression parameters.
    
    Returns:
    
    standard errors of estimated regression parameters