|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface MultipleLinearRegressionEstimator
The multiple linear regression can be represented in matrix-notation as
y=X*b+uwhere 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 | |
---|---|
void |
addData(double[] y,
double[][] x,
double[][] covariance)
Adds sample and covariance data |
double |
estimateRegressandVariance()
Returns the variance of the regressand, ie Var(y) |
double[] |
estimateRegressionParameters()
Estimates the regression parameters b |
double[][] |
estimateRegressionParametersVariance()
Estimates the variance of the regression parameters, ie Var(b) |
double[] |
estimateResiduals()
Estimates the residuals, ie u = y - X*b |
Method Detail |
---|
void addData(double[] y, double[][] x, double[][] covariance)
y
- the [n,1] array representing the y samplex
- the [n,k] array representing x samplecovariance
- the [n,n] array representing the covariance matrix or null
if not appropriate for the
specific implementationdouble[] estimateRegressionParameters()
double[][] estimateRegressionParametersVariance()
double[] estimateResiduals()
double estimateRegressandVariance()
|
||||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |