| Package | Description | 
|---|---|
| gov.sandia.cognition.statistics | 
 Provides the inheritance hierarchy for general statistical methods and distributions. 
 | 
| gov.sandia.cognition.statistics.distribution | 
 Provides statistical distributions. 
 | 
| Modifier and Type | Interface and Description | 
|---|---|
interface  | 
ClosedFormComputableDiscreteDistribution<DataType>
A discrete, closed-form Distribution with a PMF. 
 | 
interface  | 
ClosedFormDiscreteUnivariateDistribution<DomainType extends java.lang.Number>
A ClosedFormUnivariateDistribution that is also a DiscreteDistribution 
 | 
interface  | 
DataDistribution<DataType>
A distribution of data from which we can sample and perform Ring operations. 
 | 
static interface  | 
DataDistribution.PMF<KeyType>
Interface for the probability mass function (PMF) of a data distribution. 
 | 
interface  | 
IntegerDistribution
Defines a distribution over natural numbers. 
 | 
interface  | 
ProbabilityMassFunction<DataType>
The  
ProbabilityMassFunction interface defines the functionality of
 a probability mass function. | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
AbstractClosedFormIntegerDistribution
An abstract class for closed-form integer distributions. 
 | 
class  | 
AbstractDataDistribution<KeyType>
An abstract implementation of the  
DataDistribution interface. | 
| Constructor and Description | 
|---|
KullbackLeiblerDivergence(DiscreteDistribution<DomainType> firstDistribution,
                         DiscreteDistribution<DomainType> secondDistribution)
Basic constructor to find the Kullback--Leibler Divergence between the two supplied distributions. 
 | 
KullbackLeiblerDivergence(DiscreteDistribution<DomainType> firstDistribution,
                         DiscreteDistribution<DomainType> secondDistribution)
Basic constructor to find the Kullback--Leibler Divergence between the two supplied distributions. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
BernoulliDistribution
A Bernoulli distribution, which takes a value of "1" with probability "p"
 and value of "0" with probability "1-p". 
 | 
static class  | 
BernoulliDistribution.CDF
CDF of a Bernoulli distribution. 
 | 
static class  | 
BernoulliDistribution.PMF
PMF of the Bernoulli distribution. 
 | 
class  | 
BetaBinomialDistribution
A Binomial distribution where the binomial parameter, p, is set according
 to a Beta distribution instead of a single value. 
 | 
static class  | 
BetaBinomialDistribution.CDF
CDF of BetaBinomialDistribution 
 | 
static class  | 
BetaBinomialDistribution.PMF
PMF of the BetaBinomialDistribution 
 | 
class  | 
BinomialDistribution
Binomial distribution, which is a collection of Bernoulli trials 
 | 
static class  | 
BinomialDistribution.CDF
CDF of the Binomial distribution, which is the probability of getting
 up to "x" successes in "N" trials with a Bernoulli probability of "p" 
 | 
static class  | 
BinomialDistribution.PMF
The Probability Mass Function of a binomial distribution. 
 | 
class  | 
CategoricalDistribution
The Categorical Distribution is the multivariate generalization of the
 Bernoulli distribution, where the outcome of an experiment is a one-of-N
 output, where the output is a selector Vector. 
 | 
static class  | 
CategoricalDistribution.PMF
PMF of the Categorical Distribution 
 | 
class  | 
ChineseRestaurantProcess
A Chinese Restaurant Process is a discrete stochastic processes that
 partitions data points to clusters. 
 | 
static class  | 
ChineseRestaurantProcess.PMF
PMF of the Chinese Restaurant Process 
 | 
class  | 
DataCountTreeSetBinnedMapHistogram<ValueType extends java.lang.Comparable<? super ValueType>>
The  
DataCountTreeSetBinnedMapHistogram class extends a
 DefaultDataDistribution by mapping values to user defined bins
 using a TreeSetBinner. | 
class  | 
DefaultDataDistribution<KeyType>
A default implementation of  
ScalarDataDistribution that uses a
 backing map. | 
static class  | 
DefaultDataDistribution.PMF<KeyType>
PMF of the DefaultDataDistribution 
 | 
class  | 
DeterministicDistribution
A deterministic distribution that returns samples at a single point. 
 | 
static class  | 
DeterministicDistribution.CDF
CDF of the deterministic distribution. 
 | 
static class  | 
DeterministicDistribution.PMF
PMF of the deterministic distribution. 
 | 
class  | 
GeometricDistribution
The geometric distribution models the number of successes before the first
 failure occurs under an independent succession of Bernoulli tests. 
 | 
static class  | 
GeometricDistribution.CDF
CDF of the Geometric distribution 
 | 
static class  | 
GeometricDistribution.PMF
PMF of the Geometric distribution 
 | 
class  | 
MultinomialDistribution
A multinomial distribution is the multivariate/multiclass generalization
 of the Binomial distribution. 
 | 
static class  | 
MultinomialDistribution.PMF
Probability Mass Function of the Multinomial Distribution. 
 | 
class  | 
MultivariatePolyaDistribution
A multivariate Polya Distribution, also known as a Dirichlet-Multinomial
 model, is a compound distribution where the parameters of a multinomial
 are drawn from a Dirichlet distribution with fixed parameters and a constant
 number of trials and then the observations are generated by this
 multinomial. 
 | 
static class  | 
MultivariatePolyaDistribution.PMF
PMF of the MultivariatePolyaDistribution 
 | 
class  | 
NegativeBinomialDistribution
Negative binomial distribution, also known as the Polya distribution,
 gives the number of successes of a series of Bernoulli trials before
 recording a given number of failures. 
 | 
static class  | 
NegativeBinomialDistribution.CDF
CDF of the NegativeBinomialDistribution 
 | 
static class  | 
NegativeBinomialDistribution.PMF
PMF of the NegativeBinomialDistribution. 
 | 
class  | 
PoissonDistribution
A Poisson distribution is the limits of what happens when a Bernoulli trial
 with "rare" events are sampled on a continuous basis and then binned into
 discrete time intervals. 
 | 
static class  | 
PoissonDistribution.CDF
CDF of the PoissonDistribution 
 | 
static class  | 
PoissonDistribution.PMF
PMF of the PoissonDistribution. 
 | 
class  | 
ScalarDataDistribution
A Data Distribution that uses Doubles as its keys, making it a univariate
 distribution 
 | 
static class  | 
ScalarDataDistribution.CDF
CDF of the ScalarDataDistribution, maintains the keys/domain in
 sorted order (TreeMap), so it's slower than it's peers. 
 | 
static class  | 
ScalarDataDistribution.PMF
PMF of the ScalarDataDistribution 
 | 
class  | 
UniformIntegerDistribution
Contains the (very simple) definition of a continuous Uniform distribution,
 parameterized between the minimum and maximum bounds. 
 | 
static class  | 
UniformIntegerDistribution.CDF
Implements the cumulative distribution function for the discrete
 uniform distribution. 
 | 
static class  | 
UniformIntegerDistribution.PMF
Probability mass function of a discrete uniform distribution. 
 | 
class  | 
YuleSimonDistribution
The Yule-Simon distribution is a model of preferential attachment, such as
 a model of the number of groups follows a power-law distribution
 (Zipf's Law). 
 | 
static class  | 
YuleSimonDistribution.CDF
CDF of the Yule-Simon Distribution 
 | 
static class  | 
YuleSimonDistribution.PMF
PMF of the Yule-Simon Distribution 
 |