com.numericalmethod.suanshu.stats.regression.linear.logistic

Class Logistic

java.lang.Object

com.numericalmethod.suanshu.stats.regression.linear.logistic.Logistic

All Implemented Interfaces:

java.io.Serializable

public class Logistic
extends java.lang.Object
implements java.io.Serializable

A logistic regression (sometimes called the logistic model or logit model) is used for prediction of the probability of occurrence of an event by fitting data to a logit function logistic curve. It is a generalized linear model used for binomial regression.

This particular implementation works with binary data (y).

See Also:

• Wikipedia: Logistic regression
• P. J. MacCullagh and J. A. Nelder. "Likelihood functions for binary data," in Generalized Linear Models, 2nd ed. pp.114. Section 4.4."

, Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
double	AIC the AIC
Beta	beta the β^ statistics
double	ML the maximum log-likelihood
LogisticProblem	problem the logistic regression problem to be solved
Residuals	residuals the residual analysis of this regression

Constructor Summary

Constructors

Constructor and Description
Logistic(LMProblem problem) Construct a Logistic instance.

Method Summary

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

problem

public final LogisticProblem problem

the logistic regression problem to be solved

beta

public final Beta beta

the β^ statistics

residuals

public final Residuals residuals

the residual analysis of this regression

ML

public final double ML

the maximum log-likelihood

AIC

public final double AIC

the AIC

Constructor Detail

Logistic

public Logistic(LMProblem problem)
         throws java.lang.Exception

Construct a Logistic instance.

Parameters:

problem - the logistic regression problem to be solved

Throws:

java.lang.Exception