public class Data
extends java.lang.Object
Modifier and Type | Field and Description |
---|---|
static java.lang.String |
DEPENDENT_VAR |
static java.lang.String |
INDEPENDENT_VAR |
static java.lang.String |
SIGNIFICANCE_LEVEL |
Constructor and Description |
---|
Data()
NOTE:
ALL THE QUANTITATIVE DATA ARE FORCED TO CHANGE TO THE FORM OF double[].
|
Modifier and Type | Method and Description |
---|---|
void |
addPredictor(double[] data,
java.lang.String dataType) |
void |
addPredictor(float[] data,
java.lang.String dataType) |
void |
addPredictor(int[] data,
java.lang.String dataType)
appendX with two parameters
|
void |
addPredictor(long[] data,
java.lang.String dataType) |
void |
addPredictor(java.lang.String[] data,
java.lang.String dataType) |
void |
addPredictor(java.lang.String name,
double[] data,
java.lang.String dataType) |
void |
addPredictor(java.lang.String name,
java.lang.Object[] data,
java.lang.String dataType) |
void |
addPredictor(java.lang.String name,
java.lang.String[] data,
java.lang.String dataType)
appendY with three parameters
|
void |
addResponse(double[] data,
java.lang.String dataType) |
void |
addResponse(float[] data,
java.lang.String dataType) |
void |
addResponse(int[] data,
java.lang.String dataType)
appendY with two parameters
|
void |
addResponse(long[] data,
java.lang.String dataType) |
void |
addResponse(java.lang.String[] data,
java.lang.String dataType) |
void |
addResponse(java.lang.String name,
double[] data,
java.lang.String dataType) |
void |
addResponse(java.lang.String name,
java.lang.Object[] data,
java.lang.String dataType) |
void |
addResponse(java.lang.String name,
java.lang.String[] data,
java.lang.String dataType) |
void |
addSignificanceLevel(double input) |
void |
appendX(double[] data,
java.lang.String dataType) |
void |
appendX(float[] data,
java.lang.String dataType) |
void |
appendX(int[] data,
java.lang.String dataType) |
void |
appendX(long[] data,
java.lang.String dataType) |
void |
appendX(java.lang.String[] data,
java.lang.String dataType) |
void |
appendX(java.lang.String name,
double[] data,
java.lang.String dataType) |
void |
appendX(java.lang.String name,
java.lang.Object[] data,
java.lang.String dataType) |
void |
appendX(java.lang.String name,
java.lang.String[] data,
java.lang.String dataType) |
void |
appendY(double[] data,
java.lang.String dataType) |
void |
appendY(float[] data,
java.lang.String dataType) |
void |
appendY(int[] data,
java.lang.String dataType) |
void |
appendY(long[] data,
java.lang.String dataType) |
void |
appendY(java.lang.String[] data,
java.lang.String dataType) |
void |
appendY(java.lang.String name,
double[] data,
java.lang.String dataType) |
void |
appendY(java.lang.String name,
java.lang.Object[] data,
java.lang.String dataType) |
void |
appendY(java.lang.String name,
java.lang.String[] data,
java.lang.String dataType) |
Result |
getAnalysis(short analysisType) |
java.lang.String |
getAnalysisXMLInputString(short analysisType) |
double[] |
getDoubleX(java.lang.String name) |
double[] |
getDoubleY(java.lang.String name) |
java.util.HashMap<java.lang.String,Column> |
getMapX() |
java.util.HashMap<java.lang.String,Column> |
getMapY() |
NormalPowerResult |
getNormalAnalysis(double mu0,
double x,
double sigma) |
NormalPowerResult |
getNormalPower(int sampleSize,
double sigma,
double alpha,
double mu0,
double muA,
java.lang.String hypothesisType) |
NormalPowerResult |
getNormalPowerSampleSize(double power,
double sigma,
double alpha,
double mu0,
double muA,
java.lang.String hypothesisType) |
int |
getSampleSize() |
double |
getSignificanceLevel() |
SurvivalResult |
getSurvivalResult(double[] time,
byte[] censor,
java.lang.String[] groupNames) |
java.lang.Object |
getX(java.lang.String name) |
java.lang.Object |
getY(java.lang.String name) |
static void |
main(java.lang.String[] args) |
AnovaOneWayResult |
modelAnovaOneWay() |
AnovaTwoWayResult |
modelAnovaTwoWay() |
MultiLinearRegressionResult |
modelMultiLinearRegression() |
OneTResult |
modelOneT(double[] y) |
SimpleLinearRegressionResult |
modelSimpleLinearRegression()
Linear Models
|
TwoIndependentTResult |
modelTwoIndependentT(double[] x,
double[] y)
Parametric Testing
|
TwoIndependentWilcoxonResult |
modelTwoIndependentWilcoxon(double[] x,
double[] y)
Non-Parametric Testing
|
TwoPairedSignedRankResult |
modelTwoPairedSignedRank(double[] x,
double[] y) |
TwoPairedTResult |
modelTwoPairedT(double[] x,
double[] y) |
public static final java.lang.String INDEPENDENT_VAR
public static final java.lang.String DEPENDENT_VAR
public static final java.lang.String SIGNIFICANCE_LEVEL
public Data()
public void addPredictor(int[] data, java.lang.String dataType)
public void addPredictor(long[] data, java.lang.String dataType)
public void addPredictor(float[] data, java.lang.String dataType)
public void addPredictor(double[] data, java.lang.String dataType)
public void addPredictor(java.lang.String[] data, java.lang.String dataType)
public void appendX(int[] data, java.lang.String dataType)
public void appendX(long[] data, java.lang.String dataType)
public void appendX(float[] data, java.lang.String dataType)
public void addSignificanceLevel(double input)
public double getSignificanceLevel()
public void appendX(double[] data, java.lang.String dataType)
public void appendX(java.lang.String[] data, java.lang.String dataType)
public void addResponse(int[] data, java.lang.String dataType)
public void addResponse(long[] data, java.lang.String dataType)
public void addResponse(float[] data, java.lang.String dataType)
public void addResponse(double[] data, java.lang.String dataType)
public void addResponse(java.lang.String[] data, java.lang.String dataType)
public void appendY(int[] data, java.lang.String dataType)
public void appendY(long[] data, java.lang.String dataType)
public void appendY(float[] data, java.lang.String dataType)
public void appendY(double[] data, java.lang.String dataType)
public void appendY(java.lang.String[] data, java.lang.String dataType)
public void addPredictor(java.lang.String name, java.lang.String[] data, java.lang.String dataType)
public void addPredictor(java.lang.String name, double[] data, java.lang.String dataType)
public void addPredictor(java.lang.String name, java.lang.Object[] data, java.lang.String dataType)
public void appendX(java.lang.String name, java.lang.String[] data, java.lang.String dataType)
public void appendX(java.lang.String name, double[] data, java.lang.String dataType)
public void appendX(java.lang.String name, java.lang.Object[] data, java.lang.String dataType)
public void addResponse(java.lang.String name, java.lang.String[] data, java.lang.String dataType)
public void addResponse(java.lang.String name, double[] data, java.lang.String dataType)
public void addResponse(java.lang.String name, java.lang.Object[] data, java.lang.String dataType)
public void appendY(java.lang.String name, java.lang.String[] data, java.lang.String dataType)
public void appendY(java.lang.String name, double[] data, java.lang.String dataType)
public void appendY(java.lang.String name, java.lang.Object[] data, java.lang.String dataType)
public java.lang.Object getX(java.lang.String name)
public java.lang.Object getY(java.lang.String name)
public int getSampleSize()
public double[] getDoubleX(java.lang.String name)
public double[] getDoubleY(java.lang.String name)
public java.util.HashMap<java.lang.String,Column> getMapX()
public java.util.HashMap<java.lang.String,Column> getMapY()
public Result getAnalysis(short analysisType) throws java.lang.Exception
java.lang.Exception
public java.lang.String getAnalysisXMLInputString(short analysisType) throws java.lang.Exception
java.lang.Exception
public SimpleLinearRegressionResult modelSimpleLinearRegression() throws java.lang.Exception
java.lang.Exception
public MultiLinearRegressionResult modelMultiLinearRegression() throws java.lang.Exception
java.lang.Exception
public AnovaOneWayResult modelAnovaOneWay() throws java.lang.Exception
java.lang.Exception
public AnovaTwoWayResult modelAnovaTwoWay() throws java.lang.Exception
java.lang.Exception
public TwoIndependentTResult modelTwoIndependentT(double[] x, double[] y) throws java.lang.Exception
java.lang.Exception
public TwoPairedTResult modelTwoPairedT(double[] x, double[] y) throws java.lang.Exception
java.lang.Exception
public OneTResult modelOneT(double[] y) throws java.lang.Exception
java.lang.Exception
public TwoIndependentWilcoxonResult modelTwoIndependentWilcoxon(double[] x, double[] y) throws java.lang.Exception
java.lang.Exception
public TwoPairedSignedRankResult modelTwoPairedSignedRank(double[] x, double[] y) throws java.lang.Exception
java.lang.Exception
public NormalPowerResult getNormalAnalysis(double mu0, double x, double sigma) throws java.lang.Exception
java.lang.Exception
public NormalPowerResult getNormalPower(int sampleSize, double sigma, double alpha, double mu0, double muA, java.lang.String hypothesisType) throws java.lang.Exception
java.lang.Exception
public NormalPowerResult getNormalPowerSampleSize(double power, double sigma, double alpha, double mu0, double muA, java.lang.String hypothesisType) throws java.lang.Exception
java.lang.Exception
public SurvivalResult getSurvivalResult(double[] time, byte[] censor, java.lang.String[] groupNames) throws java.lang.Exception
java.lang.Exception
public static void main(java.lang.String[] args)