Uses of Class
weka.core.matrix.DoubleVector

Packages that use DoubleVector

weka.classifiers.functions.pace
weka.core.matrix

Uses of DoubleVector in weka.classifiers.functions.pace

Methods in weka.classifiers.functions.pace that return DoubleVector

DoubleVector	NormalMixture.empiricalBayesEstimate(DoubleVector x) Returns the empirical Bayes estimate of a vector.
DoubleVector	ChisqMixture.f(DoubleVector x) Computes the value of f(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.f(DoubleVector x) Computes the value of f(x) given the mixture, where x is a vector.
DoubleVector	PaceMatrix.getColumn(int j) Return a DoubleVector that stores a column of the matrix
DoubleVector	PaceMatrix.getColumn(int i0, int i1, int j) Return a DoubleVector that stores some elements of a column of the matrix
DoubleVector	ChisqMixture.h(DoubleVector AHat) Computes the value of h(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.h(DoubleVector x) Computes the value of h(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.nestedEstimate(DoubleVector x) Returns the optimal nested model estimate of a vector.
DoubleVector	PaceMatrix.nnls(PaceMatrix b, IntVector pvt) Solves the nonnegative linear squares problem.
DoubleVector	PaceMatrix.nnlse(PaceMatrix b, PaceMatrix c, PaceMatrix d, IntVector pvt) Solves the nonnegative least squares problem with equality constraint.
DoubleVector	PaceMatrix.nnlse1(PaceMatrix b, IntVector pvt) Solves the nonnegative least squares problem with equality constraint.
DoubleVector	ChisqMixture.pace2(DoubleVector x) Returns the pace2 estimate of a vector.
DoubleVector	ChisqMixture.pace4(DoubleVector x) Returns the pace4 estimate of a vector.
DoubleVector	ChisqMixture.pace6(DoubleVector x) Returns the pace6 estimate of a vector.
DoubleVector	NormalMixture.subsetEstimate(DoubleVector x) Returns the estimate of optimal subset selection.
DoubleVector	ChisqMixture.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.
DoubleVector	NormalMixture.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.
abstract DoubleVector	MixtureDistribution.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.

Methods in weka.classifiers.functions.pace with parameters of type DoubleVector

DoubleVector	NormalMixture.empiricalBayesEstimate(DoubleVector x) Returns the empirical Bayes estimate of a vector.
PaceMatrix	MixtureDistribution.empiricalProbability(DoubleVector data, PaceMatrix intervals) Computes the empirical probabilities of the data over a set of intervals.
DoubleVector	ChisqMixture.f(DoubleVector x) Computes the value of f(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.f(DoubleVector x) Computes the value of f(x) given the mixture, where x is a vector.
void	MixtureDistribution.fit(DoubleVector data) Fits the mixture (or mixing) distribution to the data.
void	MixtureDistribution.fit(DoubleVector data, int method) Fits the mixture (or mixing) distribution to the data.
DiscreteFunction	MixtureDistribution.fitForSingleCluster(DoubleVector data, int method) Fits the mixture (or mixing) distribution to the data.
PaceMatrix	ChisqMixture.fittingIntervals(DoubleVector data) Contructs the set of fitting intervals for mixture estimation.
PaceMatrix	NormalMixture.fittingIntervals(DoubleVector data) Contructs the set of fitting intervals for mixture estimation.
abstract PaceMatrix	MixtureDistribution.fittingIntervals(DoubleVector data) Contructs the set of fitting intervals for mixture estimation.
DoubleVector	ChisqMixture.h(DoubleVector AHat) Computes the value of h(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.h(DoubleVector x) Computes the value of h(x) given the mixture, where x is a vector.
DoubleVector	NormalMixture.nestedEstimate(DoubleVector x) Returns the optimal nested model estimate of a vector.
DoubleVector	ChisqMixture.pace2(DoubleVector x) Returns the pace2 estimate of a vector.
DoubleVector	ChisqMixture.pace4(DoubleVector x) Returns the pace4 estimate of a vector.
DoubleVector	ChisqMixture.pace6(DoubleVector x) Returns the pace6 estimate of a vector.
PaceMatrix	ChisqMixture.probabilityMatrix(DoubleVector s, PaceMatrix intervals) Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
PaceMatrix	NormalMixture.probabilityMatrix(DoubleVector s, PaceMatrix intervals) Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
abstract PaceMatrix	MixtureDistribution.probabilityMatrix(DoubleVector s, PaceMatrix intervals) Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.
boolean	ChisqMixture.separable(DoubleVector data, int i0, int i1, double x) Return true if a value can be considered for mixture estimation separately from the data indexed between i0 and i1
boolean	NormalMixture.separable(DoubleVector data, int i0, int i1, double x) Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
abstract boolean	MixtureDistribution.separable(DoubleVector data, int i0, int i1, double x) Return true if a value can be considered for mixture estimatino separately from the data indexed between i0 and i1
void	PaceMatrix.setMatrix(int i0, int i1, int j, DoubleVector v) Set the submatrix A[i0:i1][j] with the values stored in a DoubleVector
DoubleVector	NormalMixture.subsetEstimate(DoubleVector x) Returns the estimate of optimal subset selection.
DoubleVector	ChisqMixture.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.
DoubleVector	NormalMixture.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.
abstract DoubleVector	MixtureDistribution.supportPoints(DoubleVector data, int ne) Contructs the set of support points for mixture estimation.
void	ChisqMixture.trim(DoubleVector x) Trims the small values of the estaimte
void	NormalMixture.trim(DoubleVector x) Trims the small values of the estaimte

Constructors in weka.classifiers.functions.pace with parameters of type DoubleVector

DiscreteFunction(DoubleVector p)
Constructs a discrete function with the point values provides and the function values are all 1/n.

DiscreteFunction(DoubleVector p, DoubleVector v)
Constructs a discrete function with both the point values and function values provided.

PaceMatrix(DoubleVector v)
Construct a PaceMatrix with a single column from a DoubleVector

Uses of DoubleVector in weka.core.matrix

Methods in weka.core.matrix that return DoubleVector

DoubleVector	DoubleVector.cat(DoubleVector v) Combine two vectors together
DoubleVector	DoubleVector.copy() Makes a deep copy of the vector
DoubleVector	DoubleVector.cumulate() Returns a vector that stores the cumulated values of the original vector
DoubleVector	DoubleVector.cumulateInPlace() Cumulates the original vector in place
static DoubleVector	Maths.dchisq(double x, DoubleVector ncp) Returns the density of the noncentral Chi-squared distribution.
static DoubleVector	Maths.dchisqLog(double x, DoubleVector ncp) Returns the log-density of a set of noncentral Chi-squared distributions.
DoubleVector	DoubleVector.dividedBy(DoubleVector v) Divided by another DoubleVector element by element
DoubleVector	DoubleVector.dividedByEquals(DoubleVector v) Divided by another DoubleVector element by element in place
static DoubleVector	Maths.dnorm(double x, DoubleVector mean, double sd) Returns the density values of a set of normal distributions with different means.
static DoubleVector	Maths.dnormLog(double x, DoubleVector mean, double sd) Returns the log-density values of a set of normal distributions with different means.
DoubleVector	DoubleVector.map(String className, String method) Applies a method to the vector
DoubleVector	DoubleVector.minus(double x) Subtracts a value
DoubleVector	DoubleVector.minus(DoubleVector v) Subtracts another DoubleVector element by element
DoubleVector	DoubleVector.minusEquals(double x) Subtracts a value in place
DoubleVector	DoubleVector.minusEquals(DoubleVector v) Subtracts another DoubleVector element by element in place
static DoubleVector	Maths.pchisq(double x, DoubleVector ncp) Returns the cumulative probability of a set of noncentral Chi-squared distributions.
DoubleVector	DoubleVector.plus(double x) Adds a value to all the elements
DoubleVector	DoubleVector.plus(DoubleVector v) Adds another vector element by element
DoubleVector	DoubleVector.plusEquals(double x) Adds a value to all the elements in place
DoubleVector	DoubleVector.plusEquals(DoubleVector v) Adds another vector in place element by element
static DoubleVector	Maths.pnorm(double x, DoubleVector mean, double sd) Returns the cumulative probability of a set of normal distributions with different means.
static DoubleVector	DoubleVector.random(int n) Returns a random vector of uniform distribution
static DoubleVector	Maths.rchisq(int n, double ncp, Random random) Generates a sample of a Chi-square distribution.
DoubleVector	DoubleVector.rev() Returns the reverse vector
static DoubleVector	Maths.rnorm(int n, double mean, double sd, Random random) Generates a sample of a normal distribution.
DoubleVector	DoubleVector.sign() Returns the signs of all elements in terms of -1, 0 and +1.
DoubleVector	DoubleVector.sqrt() Returns the square-root of all the elements in the vector
DoubleVector	DoubleVector.square() Returns the squared vector
DoubleVector	DoubleVector.subvector(int i0, int i1) Returns a subvector.
DoubleVector	DoubleVector.subvector(IntVector index) Returns a subvector.
DoubleVector	DoubleVector.times(double s) Multiplies a scalar
DoubleVector	DoubleVector.times(DoubleVector v) Multiplies another DoubleVector element by element
DoubleVector	DoubleVector.timesEquals(double s) Multiply a vector by a scalar in place, u = s * u
DoubleVector	DoubleVector.timesEquals(DoubleVector v) Multiplies another DoubleVector element by element in place
DoubleVector	DoubleVector.unpivoting(IntVector index, int length) Returns a vector from the pivoting indices.

Methods in weka.core.matrix with parameters of type DoubleVector

DoubleVector	DoubleVector.cat(DoubleVector v) Combine two vectors together
static DoubleVector	Maths.dchisq(double x, DoubleVector ncp) Returns the density of the noncentral Chi-squared distribution.
static DoubleVector	Maths.dchisqLog(double x, DoubleVector ncp) Returns the log-density of a set of noncentral Chi-squared distributions.
DoubleVector	DoubleVector.dividedBy(DoubleVector v) Divided by another DoubleVector element by element
DoubleVector	DoubleVector.dividedByEquals(DoubleVector v) Divided by another DoubleVector element by element in place
static DoubleVector	Maths.dnorm(double x, DoubleVector mean, double sd) Returns the density values of a set of normal distributions with different means.
static DoubleVector	Maths.dnormLog(double x, DoubleVector mean, double sd) Returns the log-density values of a set of normal distributions with different means.
double	DoubleVector.innerProduct(DoubleVector v) Returns the inner product of two DoubleVectors
DoubleVector	DoubleVector.minus(DoubleVector v) Subtracts another DoubleVector element by element
DoubleVector	DoubleVector.minusEquals(DoubleVector v) Subtracts another DoubleVector element by element in place
static DoubleVector	Maths.pchisq(double x, DoubleVector ncp) Returns the cumulative probability of a set of noncentral Chi-squared distributions.
DoubleVector	DoubleVector.plus(DoubleVector v) Adds another vector element by element
DoubleVector	DoubleVector.plusEquals(DoubleVector v) Adds another vector in place element by element
static DoubleVector	Maths.pnorm(double x, DoubleVector mean, double sd) Returns the cumulative probability of a set of normal distributions with different means.
void	DoubleVector.set(DoubleVector v) Set the elements using a DoubleVector
void	DoubleVector.set(int i0, int i1, DoubleVector v, int j0) Set some elements using a DoubleVector.
double	DoubleVector.sum2(DoubleVector v) Returns ||u-v||^2
DoubleVector	DoubleVector.times(DoubleVector v) Multiplies another DoubleVector element by element
DoubleVector	DoubleVector.timesEquals(DoubleVector v) Multiplies another DoubleVector element by element in place