public class LogisticRegression extends Object implements LinearModel
| Constructor and Description |
|---|
LogisticRegression(LMProblem problem)
Constructs a Logistic instance.
|
LogisticRegression(LogisticProblem problem)
Constructs a Logistic instance.
|
| Modifier and Type | Method and Description |
|---|---|
double |
AIC()
Gets the AIC.
|
LogisticBeta |
beta()
Gets \(\hat{\beta}\) and statistics.
|
double |
Ey(Vector x)
Calculates the probability of occurrence (y = 1).
|
static RealScalarFunction |
logLikelihood(LogisticProblem problem)
Constructs the log-likelihood function for a logistic regression problem.
|
double |
ML()
Gets the maximum log-likelihood.
|
LogisticResiduals |
residuals()
Gets the residual analysis of an OLS regression.
|
public LogisticRegression(LogisticProblem problem)
problem - the logistic regression problem to be solvedpublic LogisticRegression(LMProblem problem)
problem - the logistic regression problem to be solvedpublic static RealScalarFunction logLikelihood(LogisticProblem problem)
public double Ey(Vector x)
Ey in interface LinearModelx - the independent variablespublic LogisticBeta beta()
LinearModelbeta in interface LinearModelpublic LogisticResiduals residuals()
LinearModelresiduals in interface LinearModelpublic double ML()
public double AIC()
Copyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.