Index (com.irurueta:irurueta-statistics 1.4.0-SNAPSHOT API)

A B C D E F G H I L M N P R S T U V W Y
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

ARTIFACT_ID_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain artifactId of this library from properties file.
artifactId - Variable in class com.irurueta.statistics.BuildInfo: ArtifactId of this library.
ASWITCH - Static variable in class com.irurueta.statistics.Gamma: Defines when to switch to quadrature method.

B

beta(double, double) - Static method in class com.irurueta.statistics.Gamma: Returns the value of the beta function B(z, w) (aka Euler integral).
bico(int, int) - Static method in class com.irurueta.statistics.Gamma: Returns the binomial coefficient (n k) as a floating-point number, which indicates the discrete probability distribution of getting exactly k successes in n trials.
branch - Variable in class com.irurueta.statistics.BuildInfo: Build branch.
BRANCH_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain build branch from properties file.
BUILD_INFO_PROPERTIES - Static variable in class com.irurueta.statistics.BuildInfo: Location of properties file that contains build data.
BUILD_NUMBER_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain build number from properties file.
BUILD_TIMESTAMP_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain build timestamp from properties file.
BuildInfo - Class in com.irurueta.statistics: Contains build data of this library.
BuildInfo() - Constructor for class com.irurueta.statistics.BuildInfo: Constructor.
buildNumber - Variable in class com.irurueta.statistics.BuildInfo: Build number.
buildTimestamp - Variable in class com.irurueta.statistics.BuildInfo: Build timestamp.

C

cdf(double) - Method in class com.irurueta.statistics.ChiSqDist: Evaluates the cumulative distribution function (c.d.f.) of this Chi-square distribution.
cdf(double) - Method in class com.irurueta.statistics.NormalDist: Evaluates the cumulative distribution function (c.d.f.) of a Gaussian distribution having the mean and standard deviation of this instance at provided point x.
cdf(double, double) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the cumulative distribution function (c.d.f.) of a Chi-squared distribution having parameter nu.
cdf(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the cumulative distribution function (c.d.f.) of a Gaussian distribution having mean mu and standard deviation sig at provided point x.
ChiSqDist - Class in com.irurueta.statistics: Contains methods to work with Chi squared distributions.
ChiSqDist(double) - Constructor for class com.irurueta.statistics.ChiSqDist: Constructor.
COF - Static variable in class com.irurueta.statistics.Erf: Coefficients of Chebychev polynomial to approximate the error function.
COF - Static variable in class com.irurueta.statistics.Gamma: Coefficients for computation of logarithm of gamma function.
com.irurueta.statistics - package com.irurueta.statistics: This package contains utility methods to generate pseudo random numbers having uniform or Gaussian distributions.
commit - Variable in class com.irurueta.statistics.BuildInfo: Build commit.
COMMIT_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain build commit from properties file.
create() - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using DEFAULT_RANDOMIZER_TYPE and USE_SECURE_RANDOM_By_DEFAULT to determine what type of random distribution is to be used and whether the random generator must be secure or not.
create(boolean) - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using DEFAULT_RANDOMIZER_TYPE.
create(RandomizerType) - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using provided randomizer type and the default secure mode specified by USE_SECURE_RANDOM_BY_DEFAULT.
create(RandomizerType, boolean) - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using provided randomizer type and provided secure mode.
create(RandomizerType, Random) - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using provided randomizer type and internal randomizer.
create(Random) - Static method in class com.irurueta.statistics.Randomizer: Creates a new Randomizer instance using provided internal randomizer instance.

D

DEFAULT_MAX_ITERATIONS - Static variable in class com.irurueta.statistics.Gamma: Default number of maximum iterations to compute incomplete gamma functions.
DEFAULT_MEAN - Static variable in class com.irurueta.statistics.GaussianRandomizer: Specifies mMean value to be used for random value generation if no mMean is provided.
DEFAULT_RANDOMIZER_TYPE - Static variable in class com.irurueta.statistics.Randomizer: Indicates default randomizer type if non is provided.
DEFAULT_STANDARD_DEVIATION - Static variable in class com.irurueta.statistics.GaussianRandomizer: Specifies standard deviation to be used for random value generation if none is provided.

E

EPS - Static variable in class com.irurueta.statistics.Gamma: Epsilon for double.
erf(double) - Static method in class com.irurueta.statistics.Erf: Evaluates the error function at x.
Erf - Class in com.irurueta.statistics: Defines the error function and methods related to it.
Erf() - Constructor for class com.irurueta.statistics.Erf: Empty constructor.
erfc(double) - Static method in class com.irurueta.statistics.Erf: Evaluates the complementary error function at x.
erfccheb(double) - Static method in class com.irurueta.statistics.Erf: Computes the complementary error function by using the Chebychev method approximation.
evaluate(double) - Method in interface com.irurueta.statistics.NormalDist.DerivativeEvaluator: Evaluates function at point x.
evaluateDerivative(double) - Method in interface com.irurueta.statistics.NormalDist.DerivativeEvaluator: Evaluates derivative of a function at point x.

F

fac - Variable in class com.irurueta.statistics.ChiSqDist: Constant factor to multiply p.d.f of chi squared by.
fac(double) - Static method in class com.irurueta.statistics.ChiSqDist: Computes constant factor to multiply p.d.f.
factln(int) - Static method in class com.irurueta.statistics.Gamma: Returns logarithm of n!
factorialsInitialized - Static variable in class com.irurueta.statistics.Gamma: Indicates whether factorials have been initialized and stored in a table for future faster access.
factorialsTable - Static variable in class com.irurueta.statistics.Gamma: Table where factorials are cached for faster future access.
factrl(int) - Static method in class com.irurueta.statistics.Gamma: Returns the factorial of n (n!) as a floating-point number.
fill(boolean[]) - Method in class com.irurueta.statistics.Randomizer: Fills provided array with random booleans.
fill(boolean[], double) - Method in class com.irurueta.statistics.GaussianRandomizer: Fills provided array with random booleans where the probability of returning true is equal to obtaining a Gaussian value below the provided threshold, which is equal to erfc function.
fill(double[]) - Method in class com.irurueta.statistics.Randomizer: Fills provided array with random double precision floating point values.
fill(double[], double) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with double precision floating point values within 0.0 and provided maxValue following a uniform distribution.
fill(double[], double, double) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform double precision floating point values within provided minValue (inclusive) and maxValue (exclusive) following a uniform distribution.
fill(float[]) - Method in class com.irurueta.statistics.Randomizer: Fills provided array with random floating point values.
fill(float[], float) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with floating point values within 0.0 and provided maxValue following a uniform distribution.
fill(float[], float, float) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform floating point values within provided minValue (inclusive) and maxValue (exclusive) following a uniform distribution.
fill(int[]) - Method in class com.irurueta.statistics.Randomizer: Fills provided array with random integer values.
fill(int[], int) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform integer values within 0 and provided maxValue following a uniform distribution.
fill(int[], int, int) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform integer values within provided minValue (inclusive) and maxValue (exclusive) following a uniform distribution.
fill(long[]) - Method in class com.irurueta.statistics.Randomizer: Fills provided array with random long values.
fill(long[], long) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform long values within 0 and provided maxValue following a uniform distribution.
fill(long[], long, long) - Method in class com.irurueta.statistics.UniformRandomizer: Fills provided array with uniform long values within provided minValue (inclusive) and maxValue (exclusive) following a uniform distribution.
FPMIN - Static variable in class com.irurueta.statistics.Gamma: Constant related to machine precision.

G

gamma - Variable in class com.irurueta.statistics.ChiSqDist: A gamma function instance to be reused for memory efficiency.
Gamma - Class in com.irurueta.statistics: Defines the gamma function, which is a function that extends the concept of factorials from natural to real and complex numbers (except zero and negative integer values).
Gamma() - Constructor for class com.irurueta.statistics.Gamma
gammln(double) - Static method in class com.irurueta.statistics.Gamma: Returns the value ln(gamma(xx)) for xx > 0.
gammp(double, double) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function P(a,x).
gammpapprox(double, double, int) - Method in class com.irurueta.statistics.Gamma: Incomplete gamma by quadrature.
gammq(double, double) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function Q(a, x) = 1 - P(a, x).
GAUSSIAN_NORM - Static variable in class com.irurueta.statistics.NormalDist: Term to normalize Gaussian so that its integral from -infinity to infinity is one.
GAUSSIAN_RANDOMIZER - Enum constant in enum class com.irurueta.statistics.RandomizerType: Type used for Gaussian randomizers where generated values are distributed following a Gaussian distribution.
GaussianRandomizer - Class in com.irurueta.statistics: Generates pseudo-random values following a Gaussian distribution having the specified mMean and standard deviation.
GaussianRandomizer() - Constructor for class com.irurueta.statistics.GaussianRandomizer: Constructor.
GaussianRandomizer(double, double) - Constructor for class com.irurueta.statistics.GaussianRandomizer: Constructor.
GaussianRandomizer(Random) - Constructor for class com.irurueta.statistics.GaussianRandomizer: Constructor.
GaussianRandomizer(Random, double, double) - Constructor for class com.irurueta.statistics.GaussianRandomizer: Constructor.
GaussLegendreQuadrature - Class in com.irurueta.statistics: Defines constants for Gauss-Legendre quadrature.
GaussLegendreQuadrature() - Constructor for class com.irurueta.statistics.GaussLegendreQuadrature: Constructor.
gcf(double, double) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function Q(a, x) evaluated by its continued fraction representation.
gcf(double, double, int) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function Q(a, x) evaluated by its continued fraction representation.
getArtifactId() - Method in class com.irurueta.statistics.BuildInfo: Obtains artifactId of this library.
getBranch() - Method in class com.irurueta.statistics.BuildInfo: Obtains build branch.
getBuildNumber() - Method in class com.irurueta.statistics.BuildInfo: Obtains build number.
getBuildTimestamp() - Method in class com.irurueta.statistics.BuildInfo: Obtains build timestamp.
getCommit() - Method in class com.irurueta.statistics.BuildInfo: Obtains build commit.
getGln() - Method in class com.irurueta.statistics.Gamma: Returns logarithm of gamma function.
getGroupId() - Method in class com.irurueta.statistics.BuildInfo: Obtains groupId of this library.
getInstance() - Static method in class com.irurueta.statistics.BuildInfo: Obtains singleton instance.
getInternalRandom() - Method in class com.irurueta.statistics.Randomizer: Returns internal instance in charge of generating pseudo-random values.
getMean() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns mMean value to be used for Gaussian random value generation.
getMean() - Method in class com.irurueta.statistics.NormalDist: Gets mean value of Gaussian distribution.
getNu() - Method in class com.irurueta.statistics.ChiSqDist: Returns nu parameter of chi square distribution.
getStandardDeviation() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns standard deviation to be used for Gaussian random value generation.
getStandardDeviation() - Method in class com.irurueta.statistics.NormalDist: Gets standard deviation of Gaussian distribution.
getType() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns the randomizer type of this instance.
getType() - Method in class com.irurueta.statistics.Randomizer: Returns the randomizer type of this instance.
getType() - Method in class com.irurueta.statistics.UniformRandomizer: Returns the randomizer type of this instance.
getVariance() - Method in class com.irurueta.statistics.NormalDist: Gets variance of Gaussian distribution.
getVersion() - Method in class com.irurueta.statistics.BuildInfo: Obtains version of this library.
gln - Variable in class com.irurueta.statistics.Gamma: Logarithm of gamma function.
GROUP_ID_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain groupID of this library from properties file.
groupId - Variable in class com.irurueta.statistics.BuildInfo: GroupId of this library.
gser(double, double) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function P(a, x) evaluated by its series representation.
gser(double, double, int) - Method in class com.irurueta.statistics.Gamma: Returns the incomplete gamma function P(a, x) evaluated by its series representation.

H

HALF_SQRT2 - Static variable in class com.irurueta.statistics.NormalDist: Square root of 2 divided by 2.

I

internalCdf(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the cumulative distribution function (c.d.f.) of a Gaussian distribution having mean mu and standard deviation sig at provided point x.
internalCdf(double, double, Gamma) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the cumulative distribution function (c.d.f.) of a Chi-squared distribution having parameter nu.
internalInvcdf(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the inverse cumulative distribution function of a Gaussian distribution having mean mu and standard deviation sig at provided point p.
internalInvcdf(double, double, Gamma) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the inverse cumulative distribution function of a Chi squared distribution having parameter nu.
internalMahalanobisDistance(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Computes the Mahalanobis distance of provided point x for provided mean and standard deviation values.
internalP(double, double, double) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the probability density function (p.d.f.) of a Chi square distribution.
internalP(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the probability density function (p.d.f.) of a Gaussian distribution having mean mu and standard deviation sig at provided point x.
internalRandom - Variable in class com.irurueta.statistics.Randomizer: Instance in charge of generating pseudo-random values.
invcdf(double) - Method in class com.irurueta.statistics.ChiSqDist: Evaluates the inverse cumulative distribution function of this Chi squared distribution.
invcdf(double) - Method in class com.irurueta.statistics.NormalDist: Evaluates the inverse cumulative distribution function of a Gaussian distribution having the mean and standard deviation of this instance at provided point p.
invcdf(double, double) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the inverse cumulative distribution function of a Chi squared distribution having parameter nu.
invcdf(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the inverse cumulative distribution function of a Gaussian distribution having mean mu and standard deviation sig at provided point p.
inverf(double) - Static method in class com.irurueta.statistics.Erf: Evaluates the inverse of the error function at p.
inverfc(double) - Static method in class com.irurueta.statistics.Erf: Evaluates the inverse of the complementary error function at p.
invgammp(double, double) - Method in class com.irurueta.statistics.Gamma: Inverse function on x of P(a, x).

L

logarithmOfFactorialsInitialized - Static variable in class com.irurueta.statistics.Gamma: Indicates whether logarithm of factorials has been initialized and stored in a table for future faster access.
logarithmOfFactorialsTable - Static variable in class com.irurueta.statistics.Gamma: Table where logarithms of factorials are cached for faster future access.
LOGGER - Static variable in class com.irurueta.statistics.BuildInfo: This class logger.

M

mahalanobisDistance(double) - Method in class com.irurueta.statistics.NormalDist: Computes the Mahalanobis distance of provided point x for current mean and standard deviation values.
mahalanobisDistance(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Computes the Mahalanobis distance of provided point x for provided mean and standard deviation values.
MAX_CACHED_LOG_FACTORIALS - Static variable in class com.irurueta.statistics.Gamma: Maximum number of logarithm of factorials cached.
MAX_FACTORIALS - Static variable in class com.irurueta.statistics.Gamma: Maximum value supported to estimate factorials for.
MaxIterationsExceededException - Exception in com.irurueta.statistics: Exception thrown when maximum number of iterations is exceeded.
MaxIterationsExceededException() - Constructor for exception com.irurueta.statistics.MaxIterationsExceededException: Constructor.
MaxIterationsExceededException(String) - Constructor for exception com.irurueta.statistics.MaxIterationsExceededException: Constructor with String containing message.
MaxIterationsExceededException(String, Throwable) - Constructor for exception com.irurueta.statistics.MaxIterationsExceededException: Constructor with message and cause.
MaxIterationsExceededException(Throwable) - Constructor for exception com.irurueta.statistics.MaxIterationsExceededException: Constructor with cause.
mean - Variable in class com.irurueta.statistics.GaussianRandomizer: Contains mMean value to be used for random value generation.
mu - Variable in class com.irurueta.statistics.NormalDist: Mean value of Gaussian distribution.

N

N_COF - Static variable in class com.irurueta.statistics.Erf: Number of coefficients to approximate the error function using a Chebychev approximation.
N_GAU - Static variable in class com.irurueta.statistics.GaussLegendreQuadrature: Length of quadrature arrays.
nextBoolean() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random boolean value.
nextBoolean() - Method in class com.irurueta.statistics.Randomizer: Returns next random boolean value following a given distribution depending on the randomizer type.
nextBoolean() - Method in class com.irurueta.statistics.UniformRandomizer: Returns next boolean value following a uniform distribution (e.g.
nextBoolean(double) - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random boolean value.
nextBooleans(int) - Method in class com.irurueta.statistics.Randomizer: Returns array of booleans.
nextBooleans(int, double) - Method in class com.irurueta.statistics.GaussianRandomizer: Returns array of booleans having provided length and containing random boolean values.
nextDouble() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random Gaussian double precision floating-point value having provided mMean and standard deviation.
nextDouble() - Method in class com.irurueta.statistics.Randomizer: Returns next random double precision floating-point value following a given distribution depending on the randomizer type.
nextDouble() - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random double precision floating-point value within the range 0.0 and 1.0 following a uniform distribution (e.g.
nextDouble(double) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random floating-point value between 0.0 and provided value following a uniform distribution (e.g.
nextDouble(double, double) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random double precision floating-point value between the range of provided values following a uniform distribution (e.g.
nextDoubles(int) - Method in class com.irurueta.statistics.Randomizer: Returns array of double precision floating point values.
nextDoubles(int, double) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform double precision floating point values within 0.0 and provided maxValue.
nextDoubles(int, double, double) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform floating point values within provided minValue and maxValue.
nextFloat() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random Gaussian floating-point value having provided mMean and standard deviation.
nextFloat() - Method in class com.irurueta.statistics.Randomizer: Returns next random floating-point value following a given distribution depending on the randomizer type.
nextFloat() - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random floating-point value within the range 0.0 and 1.0 following a uniform distribution (e.g.
nextFloat(float) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random floating-point value between 0.0 and provided value following a uniform distribution (e.g.
nextFloat(float, float) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random floating-point value between the range of provided values following a uniform distribution (e.g.
nextFloats(int) - Method in class com.irurueta.statistics.Randomizer: Returns array of floating point values.
nextFloats(int, float) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform floating point values within 0.0 and provided maxValue.
nextFloats(int, float, float) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform floating point values within provided minValue and maxValue.
nextInt() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random Gaussian integer value having provided mMean and standard deviation.
nextInt() - Method in class com.irurueta.statistics.Randomizer: Returns next random integer value following a given distribution depending on the randomizer type.
nextInt() - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random integer value within the range of integer values and following a uniform distribution (e.g.
nextInt(int) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random integer value within 0 and provided value following a uniform distribution (e.g.
nextInt(int, int) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random integer value between the range of provided values following a uniform distribution (e.g.
nextInts(int) - Method in class com.irurueta.statistics.Randomizer: Returns array of random integers.
nextInts(int, int) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform integer values within 0 and provided maxValue.
nextInts(int, int, int) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform integer values within provided minValue and maxValue.
nextLong() - Method in class com.irurueta.statistics.GaussianRandomizer: Returns next random Gaussian long value having provided mMean and standard deviation.
nextLong() - Method in class com.irurueta.statistics.Randomizer: Returns next random long value following a given distribution depending on the randomizer type.
nextLong() - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random long value within the range of long values and following a uniform distribution (e.g.
nextLong(long) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random long value within 0 and provided value following a uniform distribution (e.g.
nextLong(long, long) - Method in class com.irurueta.statistics.UniformRandomizer: Returns next random long value between the range of provided values following a uniform distribution (e.g.
nextLongs(int) - Method in class com.irurueta.statistics.Randomizer: Returns array of random long values.
nextLongs(int, long) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform long values within 0 and provided maxValue.
nextLongs(int, long, long) - Method in class com.irurueta.statistics.UniformRandomizer: Returns array of random uniform long values within provided minValue and maxValue.
NormalDist - Class in com.irurueta.statistics: Contains methods to work with normal (i.e.
NormalDist() - Constructor for class com.irurueta.statistics.NormalDist: Constructor.
NormalDist(double, double) - Constructor for class com.irurueta.statistics.NormalDist: Constructor with mean and standard deviation.
NormalDist.DerivativeEvaluator - Interface in com.irurueta.statistics: Interface to evaluate a one dimensional function at point x and to obtain its derivative at such point.
nu - Variable in class com.irurueta.statistics.ChiSqDist: Nu parameter of chi square distribution.

P

p(double) - Method in class com.irurueta.statistics.ChiSqDist: Evaluates the probability density function (p.d.f.) of this Chi square distribution.
p(double) - Method in class com.irurueta.statistics.NormalDist: Evaluates the probability density function (p.d.f.) of a Gaussian distribution having the mean and standard deviation of this instance at provided point x.
p(double, double) - Static method in class com.irurueta.statistics.ChiSqDist: Evaluates the probability density function (p.d.f.) of a Chi square distribution.
p(double, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the probability density function (p.d.f.) of a Gaussian distribution having mean mu and standard deviation sig at provided point x.
propagate(NormalDist.DerivativeEvaluator, double, double) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
propagate(NormalDist.DerivativeEvaluator, double, double, NormalDist) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
propagate(NormalDist.DerivativeEvaluator, NormalDist) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
propagate(NormalDist.DerivativeEvaluator, NormalDist, NormalDist) - Static method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
propagateThisDistribution(NormalDist.DerivativeEvaluator) - Method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at the mean point of this normal distribution and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
propagateThisDistribution(NormalDist.DerivativeEvaluator, NormalDist) - Method in class com.irurueta.statistics.NormalDist: Evaluates the derivative and a 1D function at the mean point of this normal distribution and computes the non-linear propagation of Gaussian uncertainty through such function at such point.

R

Randomizer - Class in com.irurueta.statistics: Parent class of all Randomizers.
Randomizer() - Constructor for class com.irurueta.statistics.Randomizer: Constructor.
Randomizer(Random) - Constructor for class com.irurueta.statistics.Randomizer: Constructor.
RandomizerType - Enum Class in com.irurueta.statistics: Indicates type of Randomizer.
RandomizerType() - Constructor for enum class com.irurueta.statistics.RandomizerType
reference - Static variable in class com.irurueta.statistics.BuildInfo: Singleton stored in a soft reference (to keep it cached in memory unless memory is claimed).

S

setInternalRandom(Random) - Method in class com.irurueta.statistics.Randomizer: Sets internal instance in charge of generating pseudo-random values.
setMean(double) - Method in class com.irurueta.statistics.GaussianRandomizer: Sets mMean value to be used for Gaussian random value generation.
setMean(double) - Method in class com.irurueta.statistics.NormalDist: Sets mean value of Gaussian distribution.
setNu(double) - Method in class com.irurueta.statistics.ChiSqDist: Sets nu parameter of chi square distribution.
setSeed(long) - Method in class com.irurueta.statistics.Randomizer: Sets the seed for the internal randomizer.
setStandardDeviation(double) - Method in class com.irurueta.statistics.GaussianRandomizer: Sets standard deviation to be used for Gaussian random value generation.
setStandardDeviation(double) - Method in class com.irurueta.statistics.NormalDist: Sets standard deviation of Gaussian distribution.
setVariance(double) - Method in class com.irurueta.statistics.NormalDist: Sets variance of Gaussian distribution.
sig - Variable in class com.irurueta.statistics.NormalDist: Standard deviation of Gaussian distribution.
SQRT2 - Static variable in class com.irurueta.statistics.NormalDist: Square root of 2.
standardDeviation - Variable in class com.irurueta.statistics.GaussianRandomizer: Standard deviation value to be used for random value generation.
StatisticsException - Exception in com.irurueta.statistics: Base exception for com.irurueta.statistics package.
StatisticsException() - Constructor for exception com.irurueta.statistics.StatisticsException: Constructor.
StatisticsException(String) - Constructor for exception com.irurueta.statistics.StatisticsException: Constructor with String containing message.
StatisticsException(String, Throwable) - Constructor for exception com.irurueta.statistics.StatisticsException: Constructor with message and cause.
StatisticsException(Throwable) - Constructor for exception com.irurueta.statistics.StatisticsException: Constructor with cause.

T

TIMESTAMP_FORMAT - Static variable in class com.irurueta.statistics.BuildInfo: Format for build timestamp.

U

UNIFORM_RANDOMIZER - Enum constant in enum class com.irurueta.statistics.RandomizerType: Type used for Uniform randomizers where generated values are uniformly distributed.
UniformRandomizer - Class in com.irurueta.statistics: Generates pseudo-random values following a uniform distribution.
UniformRandomizer() - Constructor for class com.irurueta.statistics.UniformRandomizer: Constructor.
UniformRandomizer(Random) - Constructor for class com.irurueta.statistics.UniformRandomizer: Constructor.
USE_SECURE_RANDOM_BY_DEFAULT - Static variable in class com.irurueta.statistics.Randomizer: Indicates that by default non-secured random instance is used if none is provided.

V

valueOf(String) - Static method in enum class com.irurueta.statistics.RandomizerType: Returns the enum constant of this class with the specified name.
values() - Static method in enum class com.irurueta.statistics.RandomizerType: Returns an array containing the constants of this enum class, in the order they are declared.
version - Variable in class com.irurueta.statistics.BuildInfo: Version of this library.
VERSION_KEY - Static variable in class com.irurueta.statistics.BuildInfo: Key to obtain version of this library from properties file.

W

W - Static variable in class com.irurueta.statistics.GaussLegendreQuadrature: W values.

Y

Y - Static variable in class com.irurueta.statistics.GaussLegendreQuadrature: Y values.

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