Uses of Class
org.drip.measure.bayesian.R1MultivariateConvolutionMetrics

Packages that use R1MultivariateConvolutionMetrics

Package	Description
org.drip.measure.bayesian	Prior, Conditional, Posterior Theil Bayesian
org.drip.portfolioconstruction.bayesian	Black Litterman Bayesian Portfolio Construction

Uses of R1MultivariateConvolutionMetrics in org.drip.measure.bayesian

Methods in org.drip.measure.bayesian that return R1MultivariateConvolutionMetrics

Modifier and Type	Method	Description
static R1MultivariateConvolutionMetrics	TheilMixedEstimationModel.GenerateComposite(ScopingProjectionVariateDistribution spvd, java.lang.String strProjection1, java.lang.String strProjection2, R1MultivariateNormal r1mnUnconditional)	Generate the Combined R^1 Multivariate Normal Distribution from the SPVD and the Named Projections
static R1MultivariateConvolutionMetrics	TheilMixedEstimationModel.GenerateComposite(ScopingProjectionVariateDistribution spvd, java.lang.String strProjection, R1MultivariateNormal r1mnUnconditional)	Generate the Combined R^1 Multivariate Normal Distribution from the SPVD, the NATIVE Projection, and the Named Projection
static R1MultivariateConvolutionMetrics	TheilMixedEstimationModel.GenerateComposite(MultivariateMeta meta, ProjectionDistributionLoading pdl1, ProjectionDistributionLoading pdl2, R1MultivariateNormal r1mnUnconditional)	Generate the Joint Mixed Estimation Model Joint/Posterior Metrics
R1MultivariateConvolutionMetrics	R1MultivariateConvolutionEngine.process(R1Multivariate rmPrior, R1Multivariate rmUnconditional, R1Multivariate rmConditional)	Generate the Joint R^1 Multivariate Combined Distribution
R1MultivariateConvolutionMetrics	R1MultivariateNormalConvolutionEngine.process(R1Multivariate r1mPrior, R1Multivariate r1mUnconditional, R1Multivariate r1mConditional)

Uses of R1MultivariateConvolutionMetrics in org.drip.portfolioconstruction.bayesian

Methods in org.drip.portfolioconstruction.bayesian that return R1MultivariateConvolutionMetrics

Modifier and Type	Method	Description
R1MultivariateConvolutionMetrics	BlackLittermanCustomConfidenceOutput.jointPosteriorMetrics()	Retrieve the Bayesian Joint/Posterior Metrics

Constructors in org.drip.portfolioconstruction.bayesian with parameters of type R1MultivariateConvolutionMetrics

Constructor	Description
BlackLittermanCustomConfidenceOutput(ForwardReverseHoldingsAllocation forwardReverseOptimizationOutput, double[] allocationAdjustmentTiltArray, R1MultivariateConvolutionMetrics jointPosteriorMetrics)	BlackLittermanCustomConfidenceOutput Constructor