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Home
Examples
Learn
API
Community
Contributing
GitHub
Twitter
YouTube
Discourse
Section Navigation
Distributions
Continuous
pymc.AsymmetricLaplace
pymc.Beta
pymc.Cauchy
pymc.ChiSquared
pymc.ExGaussian
pymc.Exponential
pymc.Flat
pymc.Gamma
pymc.Gumbel
pymc.HalfCauchy
pymc.HalfFlat
pymc.HalfNormal
pymc.HalfStudentT
pymc.Interpolated
pymc.InverseGamma
pymc.Kumaraswamy
pymc.Laplace
pymc.Logistic
pymc.LogitNormal
pymc.LogNormal
pymc.Moyal
pymc.Normal
pymc.Pareto
pymc.PolyaGamma
pymc.Rice
pymc.SkewNormal
pymc.StudentT
pymc.Triangular
pymc.TruncatedNormal
pymc.Uniform
pymc.VonMises
pymc.Wald
pymc.Weibull
Discrete
pymc.Bernoulli
pymc.BetaBinomial
pymc.Binomial
pymc.Categorical
pymc.DiscreteUniform
pymc.DiscreteWeibull
pymc.Geometric
pymc.HyperGeometric
pymc.NegativeBinomial
pymc.OrderedLogistic
pymc.OrderedProbit
pymc.Poisson
Multivariate
pymc.CAR
pymc.Dirichlet
pymc.DirichletMultinomial
pymc.ICAR
pymc.KroneckerNormal
pymc.LKJCholeskyCov
pymc.LKJCorr
pymc.MatrixNormal
pymc.Multinomial
pymc.MvNormal
pymc.MvStudentT
pymc.OrderedMultinomial
pymc.StickBreakingWeights
pymc.Wishart
pymc.WishartBartlett
pymc.ZeroSumNormal
Mixture
pymc.Mixture
pymc.NormalMixture
pymc.ZeroInflatedBinomial
pymc.ZeroInflatedNegativeBinomial
pymc.ZeroInflatedPoisson
pymc.HurdlePoisson
pymc.HurdleNegativeBinomial
pymc.HurdleGamma
pymc.HurdleLogNormal
Timeseries
pymc.AR
pymc.EulerMaruyama
pymc.GARCH11
pymc.GaussianRandomWalk
pymc.MvGaussianRandomWalk
pymc.MvStudentTRandomWalk
Truncated
Censored
Simulator
Transformations
pymc.distributions.transforms.circular
pymc.distributions.transforms.log
pymc.distributions.transforms.log_exp_m1
pymc.distributions.transforms.logodds
pymc.distributions.transforms.simplex
pymc.distributions.transforms.sum_to_1
pymc.distributions.transforms.ordered
pymc.distributions.transforms.CholeskyCovPacked
pymc.distributions.transforms.Interval
pymc.distributions.transforms.LogExpM1
pymc.distributions.transforms.Ordered
pymc.distributions.transforms.SumTo1
pymc.distributions.transforms.ZeroSumTransform
pymc.distributions.transforms.Chain
Distribution utilities
pymc.Continuous
pymc.CustomDist
pymc.Discrete
pymc.Distribution
pymc.SymbolicRandomVariable
pymc.DiracDelta
Gaussian Processes
Implementations
pymc.gp.HSGP
pymc.gp.HSGPPeriodic
pymc.gp.Latent
pymc.gp.LatentKron
pymc.gp.Marginal
pymc.gp.MarginalKron
pymc.gp.MarginalApprox
pymc.gp.TP
Mean Functions
pymc.gp.mean.Zero
pymc.gp.mean.Constant
pymc.gp.mean.Linear
Covariance Functions
pymc.gp.cov.Constant
pymc.gp.cov.WhiteNoise
pymc.gp.cov.ExpQuad
pymc.gp.cov.RatQuad
pymc.gp.cov.Exponential
pymc.gp.cov.Matern52
pymc.gp.cov.Matern32
pymc.gp.cov.Linear
pymc.gp.cov.Polynomial
pymc.gp.cov.Cosine
pymc.gp.cov.Periodic
pymc.gp.cov.WarpedInput
pymc.gp.cov.Gibbs
pymc.gp.cov.Coregion
pymc.gp.cov.ScaledCov
pymc.gp.cov.Kron
Model
Model creation and inspection
pymc.model.core.Model
pymc.model.core.modelcontext
FunctionGraph
pymc.model.fgraph.clone_model
pymc.model.fgraph.fgraph_from_model
pymc.model.fgraph.model_from_fgraph
Samplers
pymc.sample
pymc.sample_prior_predictive
pymc.sample_posterior_predictive
pymc.draw
pymc.compute_deterministics
pymc.init_nuts
pymc.sampling.jax.sample_blackjax_nuts
pymc.sampling.jax.sample_numpyro_nuts
pymc.step_methods.hmc.NUTS
pymc.step_methods.hmc.HamiltonianMC
pymc.step_methods.BinaryGibbsMetropolis
pymc.step_methods.BinaryMetropolis
pymc.step_methods.CategoricalGibbsMetropolis
pymc.step_methods.CauchyProposal
pymc.step_methods.DEMetropolis
pymc.step_methods.DEMetropolisZ
pymc.step_methods.LaplaceProposal
pymc.step_methods.Metropolis
pymc.step_methods.MultivariateNormalProposal
pymc.step_methods.NormalProposal
pymc.step_methods.PoissonProposal
pymc.step_methods.UniformProposal
pymc.step_methods.CompoundStep
pymc.step_methods.Slice
Variational Inference
pymc.ADVI
pymc.ASVGD
pymc.SVGD
pymc.FullRankADVI
pymc.ImplicitGradient
pymc.Inference
pymc.KLqp
pymc.fit
pymc.Empirical
pymc.FullRank
pymc.MeanField
pymc.sample_approx
pymc.Approximation
pymc.Group
pymc.variational.operators.KL
pymc.variational.operators.KSD
pymc.Stein
pymc.adadelta
pymc.adagrad
pymc.adagrad_window
pymc.adam
pymc.adamax
pymc.apply_momentum
pymc.apply_nesterov_momentum
pymc.momentum
pymc.nesterov_momentum
pymc.norm_constraint
pymc.rmsprop
pymc.sgd
pymc.total_norm_constraint
Sequential Monte Carlo
pymc.smc.sample_smc
pymc.smc.kernels.SMC_KERNEL
pymc.smc.kernels.IMH
pymc.smc.kernels.MH
Data
pymc.ConstantData
pymc.MutableData
pymc.get_data
pymc.Data
pymc.GeneratorAdapter
pymc.Minibatch
Ordinary differential equations (ODEs)
pymc.ode.DifferentialEquation
Probability
pymc.logp
pymc.logcdf
pymc.icdf
pymc.logprob.conditional_logp
pymc.logprob.transformed_conditional_logp
Tuning
pymc.find_hessian
pymc.find_MAP
Math
pymc.expand_packed_triangular
pymc.logit
pymc.invlogit
pymc.probit
pymc.invprobit
pymc.logaddexp
pymc.logsumexp
pymc.math.abs
pymc.math.prod
pymc.math.dot
pymc.math.eq
pymc.math.neq
pymc.math.ge
pymc.math.gt
pymc.math.le
pymc.math.lt
pymc.math.exp
pymc.math.log
pymc.math.sgn
pymc.math.sqr
pymc.math.sqrt
pymc.math.sum
pymc.math.ceil
pymc.math.floor
pymc.math.sin
pymc.math.sinh
pymc.math.arcsin
pymc.math.arcsinh
pymc.math.cos
pymc.math.cosh
pymc.math.arccos
pymc.math.arccosh
pymc.math.tan
pymc.math.tanh
pymc.math.arctan
pymc.math.arctanh
pymc.math.cumprod
pymc.math.cumsum
pymc.math.matmul
pymc.math.and_
pymc.math.broadcast_to
pymc.math.clip
pymc.math.concatenate
pymc.math.flatten
pymc.math.or_
pymc.math.stack
pymc.math.switch
pymc.math.where
pymc.math.flatten_list
pymc.math.constant
pymc.math.max
pymc.math.maximum
pymc.math.mean
pymc.math.min
pymc.math.minimum
pymc.math.round
pymc.math.erf
pymc.math.erfc
pymc.math.erfcinv
pymc.math.erfinv
pymc.math.log1pexp
pymc.math.log1mexp
pymc.math.logaddexp
pymc.math.logsumexp
pymc.math.logdiffexp
pymc.math.logit
pymc.math.invlogit
pymc.math.probit
pymc.math.invprobit
pymc.math.sigmoid
pymc.math.softmax
pymc.math.log_softmax
pymc.math.logbern
pymc.math.full
pymc.math.full_like
pymc.math.ones
pymc.math.ones_like
pymc.math.zeros
pymc.math.zeros_like
pymc.math.kronecker
pymc.math.cartesian
pymc.math.kron_dot
pymc.math.kron_solve_lower
pymc.math.kron_solve_upper
pymc.math.kron_diag
pymc.math.flat_outer
pymc.math.expand_packed_triangular
pymc.math.batched_diag
pymc.math.block_diagonal
pymc.math.matrix_inverse
pymc.math.logdet
PyTensor utils
pymc.pytensorf.compile_pymc
pymc.pytensorf.gradient
pymc.pytensorf.hessian
pymc.pytensorf.hessian_diag
pymc.pytensorf.jacobian
pymc.pytensorf.inputvars
pymc.pytensorf.cont_inputs
pymc.pytensorf.floatX
pymc.pytensorf.intX
pymc.pytensorf.smartfloatX
pymc.pytensorf.constant_fold
pymc.pytensorf.CallableTensor
pymc.pytensorf.join_nonshared_inputs
pymc.pytensorf.make_shared_replacements
pymc.pytensorf.generator
pymc.pytensorf.convert_observed_data
shape_utils
pymc.distributions.shape_utils.to_tuple
pymc.distributions.shape_utils.rv_size_is_none
pymc.distributions.shape_utils.change_dist_size
Storage backends
pymc.to_inference_data
pymc.predictions_to_inference_data
pymc.backends.NDArray
pymc.backends.base.BaseTrace
pymc.backends.base.MultiTrace
Other utils
pymc.compute_log_likelihood
pymc.compute_log_prior
pymc.find_constrained_prior
pymc.DictToArrayBijection
API
pymc.ASVGD
pymc.ASVGD.r...
pymc.ASVGD.run_profiling
#
ASVGD.
run_profiling
(
n
=
1000
,
score
=
None
,
obj_n_mc
=
500
,
**
kwargs
)
[source]
#
On this page
ASVGD.run_profiling()
Show Source
Support PyMC