com.mockturtlesolutions.snifflib.invprobs

Class Lpreg

java.lang.Object

com.mockturtlesolutions.snifflib.invprobs.Lpreg

public class Lpreg
extends java.lang.Object

Field Summary

Fields

Modifier and Type	Field and Description
DblMatrix	Alpha
AbstractBandwidthMethod	BandwidthMethod
java.lang.String	Display
int	MaxRobustIter
DblMatrix	Model
int	NumRemTerms
DblMatrix	PilotNWRSS
DblMatrix	RemTerms
AbstractWeightAlgorithm	RKernel
DblMatrix	RobustTol
DblMatrix	RWeights
AbstractWeightAlgorithm	SmoothingKernel
DblMatrix[]	sufficientX
DblMatrix	sufficientY
DblMatrix[]	X
DblMatrix	Y

Constructor Summary

Constructors

Constructor and Description
Lpreg() Empty constructor useful in updating.
Lpreg(DataSet set, java.lang.String Xvar, java.lang.String Yvar)
Lpreg(DblMatrix[] Xin, DblMatrix Yin) Basic constructor
Lpreg(DblMatrix Xin, DblMatrix Yin)

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	derivative(DblMatrix[] xx, int v)
DblMatrix	derivative(DblMatrix xx, int v)
DblMatrix	derivativeSingleThread(DblMatrix[] xx, int v) Predict derivative at the points in xx;
DblMatrix	derivativeSingleThread(DblMatrix xx, int v)
LpregDiagnostics	diagnosticsSingleThread(DblMatrix[] xx)
LpregDiagnostics	diagnosticsSingleThread(DblMatrix[] xx, int v) Get diagnostics for the prediction of the vth derivative.
AbstractBandwidthMethod	getBandwidthMethod()
DblMatrix	getGCV()
DblMatrix	getHat(DblMatrix[] xx)
DblMatrix	getModel() Return the current linear model specification.
DblMatrix[]	getXdata()
DblMatrix	getYdata()
static DblMatrix	modelDesign(DblMatrix[] X, DblMatrix model) Create a design matrix from a model matrix.
DblMatrix	predict(DblMatrix xx)
DblMatrix	predict(DblMatrix[] xx)
DblMatrix	predictConcurrent(DblMatrix xx)
DblMatrix	predictConcurrent(DblMatrix[] xx)
DblMatrix	predictSingleThread(DblMatrix[] xx)
DblMatrix	regress(DblMatrix Y, DblMatrix Design) Solve least squares problem using QR decomposition.
void	setBandwidthMethod(AbstractBandwidthMethod B) Set the bandwidth method.
void	setData(DblMatrix[] Xin, DblMatrix Yin)
void	setModel(DblMatrix m) Set the current linear model specification.
void	setSmoothingKernel(AbstractWeightAlgorithm W) Set the smoothing kernel.
void	updateRWeights()
void	useSufficient(boolean k)

Methods inherited from class java.lang.Object

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

Field Detail

X

public DblMatrix[] X

Y

public DblMatrix Y

sufficientX

public DblMatrix[] sufficientX

sufficientY

public DblMatrix sufficientY

Alpha

public DblMatrix Alpha

BandwidthMethod

public AbstractBandwidthMethod BandwidthMethod

Display

public java.lang.String Display

MaxRobustIter

public int MaxRobustIter

NumRemTerms

public int NumRemTerms

PilotNWRSS

public DblMatrix PilotNWRSS

RemTerms

public DblMatrix RemTerms

RKernel

public AbstractWeightAlgorithm RKernel

RobustTol

public DblMatrix RobustTol

RWeights

public DblMatrix RWeights

SmoothingKernel

public AbstractWeightAlgorithm SmoothingKernel

Model

public DblMatrix Model

Constructor Detail

Lpreg

public Lpreg()

Empty constructor useful in updating.

Lpreg

public Lpreg(DblMatrix Xin,
     DblMatrix Yin)

Lpreg

public Lpreg(DataSet set,
     java.lang.String Xvar,
     java.lang.String Yvar)

Lpreg

public Lpreg(DblMatrix[] Xin,
     DblMatrix Yin)

Basic constructor

Method Detail

useSufficient

public void useSufficient(boolean k)

setData

public void setData(DblMatrix[] Xin,
           DblMatrix Yin)

setModel

public void setModel(DblMatrix m)

Set the current linear model specification.

getModel

public DblMatrix getModel()

Return the current linear model specification.

getXdata

public DblMatrix[] getXdata()

getYdata

public DblMatrix getYdata()

setBandwidthMethod

public void setBandwidthMethod(AbstractBandwidthMethod B)

Set the bandwidth method. This method also calls the update method of the new BandwidthMethod and then calls the updateRWeights method.

setSmoothingKernel

public void setSmoothingKernel(AbstractWeightAlgorithm W)

Set the smoothing kernel.

getBandwidthMethod

public AbstractBandwidthMethod getBandwidthMethod()

getGCV

public DblMatrix getGCV()

getHat

public DblMatrix getHat(DblMatrix[] xx)

derivative

public DblMatrix derivative(DblMatrix[] xx,
                   int v)

derivative

public DblMatrix derivative(DblMatrix xx,
                   int v)

derivativeSingleThread

public DblMatrix derivativeSingleThread(DblMatrix xx,
                               int v)

derivativeSingleThread

public DblMatrix derivativeSingleThread(DblMatrix[] xx,
                               int v)

Predict derivative at the points in xx;

updateRWeights

public void updateRWeights()

predictConcurrent

public DblMatrix predictConcurrent(DblMatrix xx)

predictConcurrent

public DblMatrix predictConcurrent(DblMatrix[] xx)

predict

public DblMatrix predict(DblMatrix xx)

predict

public DblMatrix predict(DblMatrix[] xx)

diagnosticsSingleThread

public LpregDiagnostics diagnosticsSingleThread(DblMatrix[] xx)

diagnosticsSingleThread

public LpregDiagnostics diagnosticsSingleThread(DblMatrix[] xx,
                                       int v)

Get diagnostics for the prediction of the vth derivative.

predictSingleThread

public DblMatrix predictSingleThread(DblMatrix[] xx)

modelDesign

public static DblMatrix modelDesign(DblMatrix[] X,
                    DblMatrix model)

Create a design matrix from a model matrix.

regress

public DblMatrix regress(DblMatrix Y,
                DblMatrix Design)

Solve least squares problem using QR decomposition.