Uses of Class
org.drip.measure.continuous.R1Univariate

Packages that use R1Univariate

Package	Description
org.drip.dynamics.process	Ito-Dynamics Based Stochastic Process
org.drip.execution.bayesian	Bayesian Price Based Optimal Execution
org.drip.execution.discrete	Trajectory Slice Execution Cost Distribution
org.drip.graph.mst	Agnostic Minimum Spanning Tree Properties
org.drip.measure.bayesian	Prior, Conditional, Posterior Theil Bayesian
org.drip.measure.chisquare	Chi-Square Distribution Implementation/Properties
org.drip.measure.continuous	R1 Rd Continuous Random Measure
org.drip.measure.discrete	Antithetic, Quadratically Re-sampled, De-biased Distribution
org.drip.measure.exponential	R1 Exponential Distribution Implementation/Properties
org.drip.measure.gamma	R1 Gamma Distribution Implementation/Properties
org.drip.measure.gaussian	R1 Rd Covariant Gaussian Quadrature
org.drip.measure.lebesgue	Uniform Piece-wise Lebesgue Measure
org.drip.measure.transform	Expressing one Measure Using Another
org.drip.oms.indifference	Reservation Price Good-deal Bounds
org.drip.sequence.functional	Efron Stein Functional Supremum Bounds
org.drip.sequence.metrics	Sequence Bounds Agnostic Metrics Estimators
org.drip.sequence.random	Correlated Multi-Factor Sequence Generator
org.drip.spaces.metric	Hilbert/Banach Normed Metric Spaces
org.drip.validation.distance	Hypothesis Target Distance Test Builders

Uses of R1Univariate in org.drip.dynamics.process

Methods in org.drip.dynamics.process that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	R1StochasticEvolver.futureValueDistribution(double x0, double t)	Generate the Future Value Distribution at Time t

Uses of R1Univariate in org.drip.execution.bayesian

Subclasses of R1Univariate in org.drip.execution.bayesian

Modifier and Type	Class	Description
class	ConditionalPriceDistribution	ConditionalPriceDistribution holds the Price Distribution Conditional on a given Drift.
class	PriorDriftDistribution	PriorDriftDistribution holds the Prior Belief Distribution associated with the Directional Drift.

Uses of R1Univariate in org.drip.execution.discrete

Subclasses of R1Univariate in org.drip.execution.discrete

Modifier and Type	Class	Description
class	ShortfallIncrementDistribution	ShortfallIncrementDistribution holds the Parameters of the R1 Normal Short fall Increment Distribution.

Uses of R1Univariate in org.drip.graph.mst

Methods in org.drip.graph.mst with parameters of type R1Univariate

Modifier and Type	Method	Description
static double	SteeleCompleteUniformRandomTree.AsymptoticFriezeMSTLength(R1Univariate r1Univariate)	Compute the Length of the MST for Large n (attribution to Alan M.

Uses of R1Univariate in org.drip.measure.bayesian

Methods in org.drip.measure.bayesian that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	R1UnivariateConvolutionMetrics.conditional()	Retrieve the R1 Univariate Conditional Distribution
R1Univariate	R1UnivariateConvolutionMetrics.joint()	Retrieve the R1 Univariate Joint Distribution
R1Univariate	R1UnivariateConvolutionMetrics.posterior()	Retrieve the R1 Univariate Posterior Distribution
R1Univariate	R1UnivariateConvolutionMetrics.prior()	Retrieve the R1 Univariate Prior Distribution
R1Univariate	R1UnivariateConvolutionMetrics.unconditional()	Retrieve the R1 Univariate Unconditional Distribution

Methods in org.drip.measure.bayesian with parameters of type R1Univariate

Modifier and Type	Method	Description
R1UnivariateConvolutionMetrics	R1UnivariateConvolutionEngine.process(R1Univariate univariatePrior, R1Univariate univariateUnconditional, R1Univariate univariateConditional)	Generate the Joint R1 Univariate Combined Distribution

Constructors in org.drip.measure.bayesian with parameters of type R1Univariate

Constructor	Description
R1UnivariateConvolutionMetrics(R1Univariate prior, R1Univariate unconditional, R1Univariate conditional, R1Univariate joint, R1Univariate posterior)	R1UnivariateConvolutionMetrics Constructor

Uses of R1Univariate in org.drip.measure.chisquare

Subclasses of R1Univariate in org.drip.measure.chisquare

Modifier and Type	Class	Description
class	R1Central	R1Central implements the Probability Density Function for the R1 Central Chi-Square Distribution.
class	R1CentralCLTProxy	R1CentralCLTProxy implements the N (0, 1) CLT Proxy Version for the R1 Chi-Square Distribution.
class	R1CentralFisherProxy	R1CentralFisherProxy implements the Univariate Normal Proxy Version using the Fisher Transformation for the R1 Chi-Square Distribution.
class	R1CentralWilsonHilferty	R1CentralWilsonHilferty implements the Normal Proxy Version for the R1 Chi-Square Distribution using the Wilson-Hilferty Transfomation.
class	R1NonCentral	R1NonCentral implements the Distribution Table for the R1 Non-central Chi-Square Distribution.
class	R1NonCentralAbdelAty	R1NonCentralAbdelAty implements the Abdel-Aty (1954) Wilson-Haferty Approximation for the R1 Non-central Chi-Square Distribution.
class	R1NonCentralCLTProxy	R1NonCentralCLTProxy implements the CLT Proxy Distribution for the R1 Non-central Chi-Square Distribution.
class	R1NonCentralCumulantInvariant	R1NonCentralCumulantInvariant implements the Cumulant Invariant Transformation for the R1 Non-central Chi-Square Distribution.
class	R1NonCentralSankaran	R1NonCentralSankaran implements the Sankaran (1959, 1963) Wilson-Haferty Approximation for the R1 Non-central Chi-Square Distribution.
class	R1NonCentralWilsonHaferty	R1NonCentralWilsonHaferty implements the Wilson-Haferty Transform for the R1 Non-central Chi-Square Distribution.
class	R1WilsonHilferty	R1CentralWilsonHilferty implements the Normal Proxy Version for the R1 Chi-Square Distribution using the Wilson-Hilferty Transformation.

Uses of R1Univariate in org.drip.measure.continuous

Subclasses of R1Univariate in org.drip.measure.continuous

Modifier and Type	Class	Description
class	R1ParetoDistribution	R1ParetoDistribution implements the R1 Pareto Distribution.
class	R1PowerLawDistribution	R1PowerLawDistribution implements the R1 Power Law Distribution.
class	R1UnivariateUniform	R1UnivariateUniform implements the Univariate R1 Uniform Distribution.

Methods in org.drip.measure.continuous with parameters of type R1Univariate

Modifier and Type	Method	Description
double	R1Univariate.kullbackLeiblerDivergence(R1Univariate r1UnivariateOther)	Compute the Kullback-Leibler Divergence against the other R1 Distribution

Uses of R1Univariate in org.drip.measure.discrete

Subclasses of R1Univariate in org.drip.measure.discrete

Modifier and Type	Class	Description
class	BoundedUniformIntegerDistribution	BoundedUniformIntegerDistribution implements the Univariate Bounded Uniform Integer Distribution, with the Integer being generated between a (n inclusive) lower and an upper Bound.
class	PoissonDistribution	PoissonDistribution implements the Univariate Poisson Distribution using the specified Mean/Variance.

Uses of R1Univariate in org.drip.measure.exponential

Subclasses of R1Univariate in org.drip.measure.exponential

Modifier and Type	Class	Description
class	R1RateDistribution	R1RateDistribution implements the Rate Parameterization of the R1 Exponential Distribution.
class	R1ScaledDistribution	R1ScaledDistribution implements the Probability Density Function for the Scaled R1 Exponential Function.
class	RealizedMinimaR1RateDistribution	RealizedMinimaR1RateDistribution implements the Rate Parameterization of the Realized Minimum among the Set of R1 Exponential Distributions.
class	TwoIIDSum	TwoIIDSum implements the PDF of the Sum of Two IID Exponential Random Variables.

Methods in org.drip.measure.exponential with parameters of type R1Univariate

Modifier and Type	Method	Description
double	R1RateDistribution.kullbackLeiblerDivergence(R1Univariate r1UnivariateOther)

Uses of R1Univariate in org.drip.measure.gamma

Subclasses of R1Univariate in org.drip.measure.gamma

Modifier and Type	Class	Description
class	ErlangDistribution	ErlangDistribution implements the Shape and Scale Parameterization of the R1 Erlang Distribution.
class	R1ShapeScaleDiscrete	R1ShapeScaleDiscrete generates Discrete Variables that are Derivatives of the R1 Gamma Distribution.
class	R1ShapeScaleDistribution	R1ShapeScaleDistribution implements the Shape and Scale Parameterization of the R1 Gamma Distribution.

Uses of R1Univariate in org.drip.measure.gaussian

Subclasses of R1Univariate in org.drip.measure.gaussian

Modifier and Type	Class	Description
class	R1UnivariateNormal	R1UnivariateNormal implements the Univariate R1 Normal Distribution.

Uses of R1Univariate in org.drip.measure.lebesgue

Subclasses of R1Univariate in org.drip.measure.lebesgue

Modifier and Type	Class	Description
class	R1PiecewiseDisplaced	R1PiecewiseDisplaced implements the Displaced Piecewise Linear R1 Distributions.
class	R1PiecewiseLinear	R1PiecewiseLinear implements the Piecewise Linear R1 Distributions.
class	R1Uniform	R1Uniform implements the R1 Lebesgue (i.e., Bounded Uniform) Distribution, with a Uniform Distribution between a Lower and an Upper Bound.

Uses of R1Univariate in org.drip.measure.transform

Subclasses of R1Univariate in org.drip.measure.transform

Modifier and Type	Class	Description
class	R1GammaToExponential	R1GammaToExponential implements the R1 Exponential Distribution in Terms of the R1 Gamma Distribution.
class	R1GammaToMaxwellBoltzmannSquared	R1GammaToMaxwellBoltzmannSquared implements the Maxwell-Boltzmann Squared Distribution using the R1 Gamma Distribution.

Uses of R1Univariate in org.drip.oms.indifference

Methods in org.drip.oms.indifference with parameters of type R1Univariate

Modifier and Type	Method	Description
double	ReservationPricer.askClaimsPositionValueAdjustment(R1Univariate underlierPriceDistribution, double moneyMarketPrice, double noClaimsInventoryUtilityExpectation)	Compute the Ask Claims Inventory-based Position Value Adjustment
double	ReservationPricer.bidClaimsPositionValueAdjustment(R1Univariate underlierPriceDistribution, double moneyMarketPrice, double noClaimsInventoryUtilityExpectation)	Compute the Bid Claims Inventory-based Position Value Adjustment
ClaimsUtilityExpectationInferenceRun	UtilityFunctionExpectation.inferPositionAdjustment(R1Univariate underlierPriceDistribution, double targetUtilityExpectationValue)	Run the Position Adjustment Inference for the Claims given the Target Utility Expectation Value
double	ReservationPricer.noClaimsInventoryUtilityExpectation(R1Univariate underlierPriceDistribution, double moneyMarketPrice)	Compute the No-Claims Inventory-based Optimal Utility Value
UtilityExpectationOptimizationRun	UtilityFunctionExpectation.optimizationRun(R1Univariate underlierPriceDistribution, double positionValueAdjustment)	Generate the Utility Expectation Optimization Run given the Underlier Price Distribution
ReservationPricingRun	ReservationPricer.reservationPricingRun(R1Univariate underlierPriceDistribution, double moneyMarketPrice)	Run a Reservation Pricing Flow

Uses of R1Univariate in org.drip.sequence.functional

Methods in org.drip.sequence.functional that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	FunctionSupremumUnivariateRandom.underlyingDistribution()	Retrieve the Underlying Distribution
R1Univariate	IdempotentUnivariateRandom.underlyingDistribution()	Retrieve the Underlying Distribution

Constructors in org.drip.sequence.functional with parameters of type R1Univariate

Constructor	Description
BinaryIdempotentUnivariateRandom(double dblOffset, R1Univariate dist, double dblVariateBound, double dblPositiveProbability)	BinaryIdempotentUnivariateRandom Constructor
BoundedIdempotentUnivariateRandom(double dblOffset, R1Univariate dist, double dblVariateBound)	BoundedIdempotentUnivariateRandom Constructor
FunctionSupremumUnivariateRandom(R1ToR1[] aAUClass, R1Univariate dist)	FunctionSupremumUnivariateRandom Constructor
IdempotentUnivariateRandom(double dblOffset, R1Univariate dist)	IdempotentUnivariateRandom Constructor

Uses of R1Univariate in org.drip.sequence.metrics

Methods in org.drip.sequence.metrics that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	SingleSequenceAgnosticMetrics.populationDistribution()	Retrieve the Population Distribution

Constructors in org.drip.sequence.metrics with parameters of type R1Univariate

Constructor	Description
BoundedSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation, double dblSupport)	BoundedSequenceAgnosticMetrics Constructor
IntegerSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation)	Build out the Sequence and their Metrics
SingleSequenceAgnosticMetrics(double[] adblSequence, R1Univariate distPopulation)	Build out the Sequence and their Metrics

Uses of R1Univariate in org.drip.sequence.random

Methods in org.drip.sequence.random with parameters of type R1Univariate

Modifier and Type	Method	Description
SingleSequenceAgnosticMetrics	Bounded.sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics	BoundedUniformInteger.sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics	Poisson.sequence(int iNumEntry, R1Univariate distPopulation)
SingleSequenceAgnosticMetrics	UnivariateSequenceGenerator.sequence(int iNumEntry, R1Univariate distPopulation)	Generate a Random Sequence along with its Metrics

Uses of R1Univariate in org.drip.spaces.metric

Methods in org.drip.spaces.metric that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	R1Combinatorial.borelSigmaMeasure()
R1Univariate	R1Continuous.borelSigmaMeasure()
R1Univariate	R1Normed.borelSigmaMeasure()	Retrieve the Borel Sigma R1 Probability Measure

Methods in org.drip.spaces.metric with parameters of type R1Univariate

Modifier and Type	Method	Description
static R1CombinatorialBall	R1CombinatorialBall.ClosedUnit(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm)	Construct a R1CombinatorialBall Instance of Unit Radius
static R1ContinuousBall	R1ContinuousBall.ClosedUnit(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm)	Construct a R1ContinuousBall Instance of Unit Radius
static R1Combinatorial	R1Combinatorial.Standard(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1, int iPNorm)	Construct the Standard lp R1 Combinatorial Space Instance
static R1Continuous	R1Continuous.Standard(double dblLeftEdge, double dblRightEdge, R1Univariate distR1, int iPNorm)	Construct the Standard lp R1 Continuous Space Instance
static R1Combinatorial	R1Combinatorial.Supremum(java.util.List<java.lang.Double> lsElementSpace, R1Univariate distR1)	Construct the Supremum (i.e., lInfinity) R1 Combinatorial Space Instance
static R1Continuous	R1Continuous.Supremum(double dblLeftEdge, double dblRightEdge, R1Univariate distR1)	Construct the Supremum (i.e., lInfinity) R1 Continuous Space Instance

Constructors in org.drip.spaces.metric with parameters of type R1Univariate

Constructor	Description
R1Combinatorial(java.util.List<java.lang.Double> elementSpaceList, R1Univariate r1Distribution, int pNorm)	R1Combinatorial Space Constructor
R1CombinatorialBall(java.util.List<java.lang.Double> elementSpaceList, R1Univariate r1Distribution, int pNorm, double normRadius)	R1CombinatorialBall Constructor
R1Continuous(double leftEdge, double rightEdge, R1Univariate r1Univariate, int pNorm)	R1Continuous Space Constructor
R1ContinuousBall(double leftEdge, double rightEdge, R1Univariate r1Univariate, int pNorm, double normRadius)	R1ContinuousBall Constructor

Uses of R1Univariate in org.drip.validation.distance

Methods in org.drip.validation.distance that return R1Univariate

Modifier and Type	Method	Description
R1Univariate	ImportanceWeight.r1Univariate()	Retrieve the Underlying R1 Distribution

Constructors in org.drip.validation.distance with parameters of type R1Univariate

Constructor	Description
ImportanceWeight(R1Univariate r1Univariate, double positiveExpectation)	ImportanceWeight Constructor