edu.ucla.stat.SOCR.modeler
Class LogNormalFit_Modeler

java.lang.Object
  edu.ucla.stat.SOCR.modeler.Modeler
      edu.ucla.stat.SOCR.modeler.LogNormalFit_Modeler

All Implemented Interfaces:

java.awt.event.ItemListener, java.util.EventListener

public class LogNormalFit_Modeler
extends Modeler
implements java.awt.event.ItemListener

Field Summary

javax.swing.JCheckBox	estimateParams
LogNormalDistribution	LogNormalDistr
javax.swing.JTextField	meanParamField
javax.swing.JLabel	meanParamLabel
javax.swing.JTextField	SDParamField
javax.swing.JLabel	SDParamLabel
static int	SLICE_SIZE
javax.swing.JCheckBox	userParams

Fields inherited from class edu.ucla.stat.SOCR.modeler.Modeler

CONTINUOUS_DISTRIBUTION_TYPE, DISCRETE_DISTRIBUTION_TYPE, FOURIER_TYPE, MIXED_DISTRIBUTION_TYPE, WAVELET_TYPE

Constructor Summary

LogNormalFit_Modeler()

LogNormalFit_Modeler(javax.swing.JPanel controlpanel)

Method Summary

void	addParams(javax.swing.JPanel controlpanel)
void	fitCurve(float[] rawDat, double minx, double maxx, javax.swing.JTextArea resultPanelTextArea, boolean rescaleClicked, boolean scaleUp, boolean initReset) takes data along with x, y limits and fits a pdf to the data range and stores the resulting model fit in data arrays that must be returned by calls to returnModelX() and returnModelY()
void	fitCurve(float[] rawDat, float minx, float maxx, javax.swing.JTextArea resultPanelTextArea, boolean rescaleClicked, boolean scaleUp, boolean initReset)
double[]	generateSamples(int sampleCount) generates samples from the distribution and returns a double[] data type
java.lang.String	getDescription() return the description for this modeler
double	getGraphLowerLimit()
double	getGraphUpperLimit()
java.lang.String	getInstructions() return the instructions for using this modeler
double	getLowerLimit() return the allowable x limit values.
int	getModelCount() return the number of models to be plotted.
int	getModelType() returns one if model is of distribution and needs to be rescaled for display.
java.lang.String	getResearch() return the references for this modeler
double	getUpperLimit() return the allowaable x limit values.
boolean	isContinuous()
void	itemStateChanged(java.awt.event.ItemEvent event)
void	registerObservers(ObservableWrapper o)
double[]	returnModelX() returns the fitted model values for X axis
double[]	returnModelY() returns the fitted densisty for corresponding X axis values
void	toggleParams(boolean istrue)
boolean	useInitButton() What is this method used for?

Methods inherited from class edu.ucla.stat.SOCR.modeler.Modeler

getKSModelTestString

Methods inherited from class java.lang.Object

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

Field Detail

LogNormalDistr

public LogNormalDistribution LogNormalDistr

SLICE_SIZE

public static final int SLICE_SIZE

See Also:

Constant Field Values

estimateParams

public javax.swing.JCheckBox estimateParams

userParams

public javax.swing.JCheckBox userParams

meanParamLabel

public javax.swing.JLabel meanParamLabel

meanParamField

public javax.swing.JTextField meanParamField

SDParamLabel

public javax.swing.JLabel SDParamLabel

SDParamField

public javax.swing.JTextField SDParamField

Constructor Detail

LogNormalFit_Modeler

public LogNormalFit_Modeler()

LogNormalFit_Modeler

public LogNormalFit_Modeler(javax.swing.JPanel controlpanel)

Method Detail

addParams

public void addParams(javax.swing.JPanel controlpanel)

fitCurve

public void fitCurve(float[] rawDat,
                     double minx,
                     double maxx,
                     javax.swing.JTextArea resultPanelTextArea,
                     boolean rescaleClicked,
                     boolean scaleUp,
                     boolean initReset)

Description copied from class: Modeler

takes data along with x, y limits and fits a pdf to the data range and stores the resulting model fit in data arrays that must be returned by calls to returnModelX() and returnModelY()

Overrides:

fitCurve in class Modeler

fitCurve

public void fitCurve(float[] rawDat,
                     float minx,
                     float maxx,
                     javax.swing.JTextArea resultPanelTextArea,
                     boolean rescaleClicked,
                     boolean scaleUp,
                     boolean initReset)

generateSamples

public double[] generateSamples(int sampleCount)

Description copied from class: Modeler

generates samples from the distribution and returns a double[] data type

Overrides:

generateSamples in class Modeler

getDescription

public java.lang.String getDescription()

Description copied from class: Modeler

return the description for this modeler

Overrides:

getDescription in class Modeler

getGraphLowerLimit

public double getGraphLowerLimit()

Overrides:

getGraphLowerLimit in class Modeler

getGraphUpperLimit

public double getGraphUpperLimit()

Overrides:

getGraphUpperLimit in class Modeler

getInstructions

public java.lang.String getInstructions()

Description copied from class: Modeler

return the instructions for using this modeler

Overrides:

getInstructions in class Modeler

getLowerLimit

public double getLowerLimit()

Description copied from class: Modeler

return the allowable x limit values. This method should return the lower limit. eg: for a normal distribution lowerlimit = NEGATIVE_INFINITY

Overrides:

getLowerLimit in class Modeler

getModelCount

public int getModelCount()

Description copied from class: Modeler

return the number of models to be plotted. If n models are returned, the vectors from returnModelX and returnModelY will be split into n equal sub sections and plotted

Overrides:

getModelCount in class Modeler

Returns:

getModelType

public int getModelType()

Description copied from class: Modeler

returns one if model is of distribution and needs to be rescaled for display. Returns 0 if model does not require scaling. EG: Polynomial fit is type 0 and normal distribution is type 1.

Overrides:

getModelType in class Modeler

getResearch

public java.lang.String getResearch()

Description copied from class: Modeler

return the references for this modeler

Overrides:

getResearch in class Modeler

getUpperLimit

public double getUpperLimit()

Description copied from class: Modeler

return the allowaable x limit values. This method should return the upper limit. eg: for a normal distribution upperlimit = POSITIVE_INFINITY

Overrides:

getUpperLimit in class Modeler

isContinuous

public boolean isContinuous()

Overrides:

isContinuous in class Modeler

itemStateChanged

public void itemStateChanged(java.awt.event.ItemEvent event)

Specified by:

itemStateChanged in interface java.awt.event.ItemListener

registerObservers

public void registerObservers(ObservableWrapper o)

Overrides:

registerObservers in class Modeler

returnModelX

public double[] returnModelX()

Description copied from class: Modeler

returns the fitted model values for X axis

Overrides:

returnModelX in class Modeler

returnModelY

public double[] returnModelY()

Description copied from class: Modeler

returns the fitted densisty for corresponding X axis values

Overrides:

returnModelY in class Modeler

toggleParams

public void toggleParams(boolean istrue)

useInitButton

public boolean useInitButton()

Description copied from class: Modeler

What is this method used for?

Overrides:

useInitButton in class Modeler