Functionality for diagnosing samples generated using Markov Chain Monte Carlo.
This package is a joint collaboration between the Turing and ArviZ projects.
- Popularity
- 19 Stars
- Updated Last
- 4 Months Ago
- Started In
- May 2021
Required Packages
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AbstractFFTs
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AliasTables
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ChainRulesCore
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ChangesOfVariables
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Compat
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DataAPI
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DataStructures
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DataValueInterfaces
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DensityInterface
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Distributions
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DocStringExtensions
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FillArrays
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HypergeometricFunctions
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InverseFunctions
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IrrationalConstants
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IteratorInterfaceExtensions
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LogExpFunctions
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Missings
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MLJModelInterface
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OrderedCollections
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PDMats
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PtrArrays
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QuadGK
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Reexport
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Rmath
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ScientificTypesBase
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SortingAlgorithms
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SparseArrays
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SpecialFunctions
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StatisticalTraits
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StatsAPI
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StatsBase
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StatsFuns
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Tables
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TableTraits
Used By Packages
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ActionModels
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ActiveInference
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AdditiveCellCom
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AnimalBehavior
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ArviZ
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ArviZPythonPlots
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BarBay
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BayesFlux
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BayesianNetworkRegression
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BayesQR
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Baytes
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BaytesInference
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BOSS
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CalibrateEmulateSample
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CMBLensing
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CRRao
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DiffEqBayes
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DiffEqBayesStan
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DiffEqTutorials
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DifferentialEvolutionMCMC
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DistributedStwdLDA
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DynamicHMCExamples
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Dynare
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EasyModelAnalysis
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EqualitySampler
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Firefly
-
HierarchicalGaussianFiltering
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InferenceReport
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Jags
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LogDensityTestSuite
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MambaModels
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MCMCBenchmarks
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MCMCChains
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MCMCChainsStorage
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MCMCTempering
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MicroCanonicalHMC
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NestedSamplers
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NeuralPDE
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Octofitter
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ParetoSmooth
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Pioran
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Plasma
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PosteriorPlots
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PosteriorStats
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ProbabilisticEchoInversion
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ProbabilisticParameterEstimators
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RegressionAndOtherStories
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SafetySignalDetection
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ShipMMG
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SideKicks
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SimulatedNeuralMoments
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SimulationBasedInference
View all packages