Apache Commons Math 3.6.1 · org.apache.commons.math3.stat.regression.UpdatingMultipleLinearRegression

Method Summary

Modifier and Type	Method and Description
public void	addObservation(double[] the independent variables which form the design matrix x, double the dependent or response variable y) Adds one observation to the regression model.
public void	addObservations(double[][] a series of observations on the independent variables x, double[] a series of observations on the dependent variable The length of x and y must be the same y) Adds a series of observations to the regression model.
public void	clear() Clears internal buffers and resets the regression model.
public long	Returns: Number of observations getN() Returns the number of observations added to the regression model.
public boolean	Returns: true if constant exists, false otherwise hasIntercept() Returns true if a constant has been included false otherwise.
public RegressionResults	Returns: RegressionResults acts as a container of regression output regress() Performs a regression on data present in buffers and outputs a RegressionResults object
public RegressionResults	Returns: RegressionResults acts as a container of regression output regress(int[] an array of indices of regressors to include variablesToInclude) Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object

Method Detail

addObservation back to summary

addObservation	back to summary
public void addObservation(double[] x, double y) throws ModelSpecificationException Adds one observation to the regression model. Parameters x:double[] the independent variables which form the design matrix y:double the dependent or response variable Exceptions ModelSpecificationException: if the length of `x` does not equal the number of independent variables in the model

public void addObservation(double[] x, double y) throws ModelSpecificationException

Adds one observation to the regression model.

Parameters

x:double[]: the independent variables which form the design matrix
y:double: the dependent or response variable

Exceptions

ModelSpecificationException:: if the length of x does not equal the number of independent variables in the model

addObservations back to summary

addObservations	back to summary
public void addObservations(double[][] x, double[] y) throws ModelSpecificationException Adds a series of observations to the regression model. The lengths of x and y must be the same and x must be rectangular. Parameters x:double[][] a series of observations on the independent variables y:double[] a series of observations on the dependent variable The length of x and y must be the same Exceptions ModelSpecificationException: if `x` is not rectangular, does not match the length of `y` or does not contain sufficient data to estimate the model

public void addObservations(double[][] x, double[] y) throws ModelSpecificationException

Adds a series of observations to the regression model. The lengths of x and y must be the same and x must be rectangular.

Parameters

x:double[][]: a series of observations on the independent variables
y:double[]: a series of observations on the dependent variable The length of x and y must be the same

Exceptions

ModelSpecificationException:: if x is not rectangular, does not match the length of y or does not contain sufficient data to estimate the model

clear	back to summary
public void clear() Clears internal buffers and resets the regression model. This means all data and derived values are initialized

getN	back to summary
public long getN() Returns the number of observations added to the regression model. Returns:long Number of observations

getN

back to summary

public long getN()

Returns the number of observations added to the regression model.

Returns:long: Number of observations

hasIntercept	back to summary
public boolean hasIntercept() Returns true if a constant has been included false otherwise. Returns:boolean true if constant exists, false otherwise

hasIntercept

back to summary

public boolean hasIntercept()

Returns true if a constant has been included false otherwise.

Returns:boolean: true if constant exists, false otherwise

regress	back to summary
public RegressionResults regress() throws ModelSpecificationException, NoDataException Performs a regression on data present in buffers and outputs a RegressionResults object Returns:RegressionResults RegressionResults acts as a container of regression output Exceptions ModelSpecificationException: if the model is not correctly specified NoDataException: if there is not sufficient data in the model to estimate the regression parameters

regress

back to summary

public RegressionResults regress() throws ModelSpecificationException, NoDataException

Performs a regression on data present in buffers and outputs a RegressionResults object

Returns:RegressionResults

RegressionResults acts as a container of regression output

Exceptions

ModelSpecificationException:: if the model is not correctly specified
NoDataException:: if there is not sufficient data in the model to estimate the regression parameters

regress	back to summary
public RegressionResults regress(int[] variablesToInclude) throws ModelSpecificationException, MathIllegalArgumentException Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object Parameters variablesToInclude:int[] an array of indices of regressors to include Returns:RegressionResults RegressionResults acts as a container of regression output Exceptions ModelSpecificationException: if the model is not correctly specified MathIllegalArgumentException: if the variablesToInclude array is null or zero length

regress

back to summary

public RegressionResults regress(int[] variablesToInclude) throws ModelSpecificationException, MathIllegalArgumentException

Performs a regression on data present in buffers including only regressors indexed in variablesToInclude and outputs a RegressionResults object

Parameters

variablesToInclude:int[]: an array of indices of regressors to include

Returns:RegressionResults

RegressionResults acts as a container of regression output

Exceptions

ModelSpecificationException:: if the model is not correctly specified
MathIllegalArgumentException:: if the variablesToInclude array is null or zero length

public Interface UpdatingMultipleLinearRegression

Method Summary

Method Detail