public class AnalysisUtility
extends java.lang.Object
Modifier and Type | Field and Description |
---|---|
static java.lang.String |
closeToZero |
static double |
HIGH_CORRELATION |
static int |
NUMBER_OF_DUMMY_DIGITS |
static double |
PRECISION_TOLERANCE |
Constructor and Description |
---|
AnalysisUtility() |
Modifier and Type | Method and Description |
---|---|
static boolean |
dataColinear(double[] x,
double[] y) |
static double[] |
diff(double[] data) |
static Matrix |
eliminationGaussJordan(Matrix matrixInput) |
static java.lang.String |
enhanceSmallNumber(double original) |
static int |
factorial(int input) |
static java.math.BigInteger |
factorialBigInt(int input) |
static double |
functionRootBrentDekker(double a,
double b,
MathFunction f,
double tol)
Computes a root of the function using the Brent-Dekker method.
|
static byte[][] |
getDummyMatrix(java.lang.String[] groups) |
static double[] |
getGenericNormalQuantile(double mean,
double sd,
int m) |
static double |
getNormalCriticalPoint(double alpha) |
static double[] |
getNormalQuantile(int m) |
static double[] |
getQuantileArray(double[] input) |
static java.util.HashMap<java.lang.String,java.lang.Object> |
getResidualNormalQuantiles(double[] residual,
int degreesFreedom) |
static DataCase[] |
getSortedRedidual(double[] residual) |
static double[] |
getStandardizedResidual(DataCase[] residual,
int df) |
static double[] |
getStandardizedResidual(double[] residual,
int degreesFreedom) |
static double[] |
getStandardNormalQuantile(int m) |
static double |
getStudentTCriticalPoint(double alpha,
int df) |
static Matrix |
inverse(Matrix matrix) |
static java.util.LinkedHashSet<java.lang.String> |
levelFactor(java.lang.String[] x) |
static java.util.TreeSet<java.lang.String> |
levelFactorTree(java.lang.String[] x) |
static void |
main(java.lang.String[] args) |
static double |
mean(double[] data) |
static double |
meanSquaredError(double[] data,
int degreesFreedom) |
static java.math.BigInteger |
product(java.math.BigInteger[] data) |
static double |
product(double[] data) |
static double |
sampleCorrelation(double[] dataX,
double[] dataY) |
static double |
sampleCovariance(double[] dataX,
double[] dataY) |
static double |
sampleVariance(double[] data) |
static double |
sum(double[] data) |
static double |
sumOfSquares(double[] data) |
static double |
sumPossitiveIntegerSequenceFromOne(int end) |
static double |
sumPossitiveIntegerSequencePartial(int start,
int end) |
static java.lang.String[][] |
truncateDigits(double[][] input,
int numberDigits) |
static java.lang.String[] |
truncateDigits(double[] input,
int numberDigits) |
static java.lang.String |
truncateDigits(double input,
int numberDigits)
CODE EXAMPLE
|
static double |
variance(double[] data) |
public static final double PRECISION_TOLERANCE
public static final java.lang.String closeToZero
public static final double HIGH_CORRELATION
public static final int NUMBER_OF_DUMMY_DIGITS
public static double sum(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static java.math.BigInteger product(java.math.BigInteger[] data) throws DataIsEmptyException
DataIsEmptyException
public static double product(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double mean(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double[] diff(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double sumOfSquares(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double sampleVariance(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double variance(double[] data) throws DataIsEmptyException
DataIsEmptyException
public static double meanSquaredError(double[] data, int degreesFreedom) throws DataIsEmptyException
DataIsEmptyException
public static double sampleCovariance(double[] dataX, double[] dataY) throws DataIsEmptyException
DataIsEmptyException
public static double sampleCorrelation(double[] dataX, double[] dataY) throws DataIsEmptyException
DataIsEmptyException
public static double[] getNormalQuantile(int m)
public static double[] getStandardNormalQuantile(int m)
public static double[] getGenericNormalQuantile(double mean, double sd, int m)
public static double[] getQuantileArray(double[] input)
public static java.util.HashMap<java.lang.String,java.lang.Object> getResidualNormalQuantiles(double[] residual, int degreesFreedom)
public static DataCase[] getSortedRedidual(double[] residual)
public static double[] getStandardizedResidual(DataCase[] residual, int df) throws DataIsEmptyException
DataIsEmptyException
public static double[] getStandardizedResidual(double[] residual, int degreesFreedom) throws DataIsEmptyException
DataIsEmptyException
public static java.util.TreeSet<java.lang.String> levelFactorTree(java.lang.String[] x)
public static java.util.LinkedHashSet<java.lang.String> levelFactor(java.lang.String[] x)
public static byte[][] getDummyMatrix(java.lang.String[] groups)
public static java.math.BigInteger factorialBigInt(int input)
public static int factorial(int input)
public static double sumPossitiveIntegerSequencePartial(int start, int end)
public static double sumPossitiveIntegerSequenceFromOne(int end)
public static java.lang.String enhanceSmallNumber(double original)
public static boolean dataColinear(double[] x, double[] y)
public static java.lang.String truncateDigits(double input, int numberDigits)
public static java.lang.String[] truncateDigits(double[] input, int numberDigits)
public static java.lang.String[][] truncateDigits(double[][] input, int numberDigits)
public static double getNormalCriticalPoint(double alpha)
public static double getStudentTCriticalPoint(double alpha, int df)
public static double functionRootBrentDekker(double a, double b, MathFunction f, double tol)
a
- left endpoint of initial intervalb
- right endpoint of initial intervalf
- the function which is evaluatedtol
- accuracy goalpublic static void main(java.lang.String[] args)