inference-tools
stable
Contents:
Getting started
Markov-chain Monte-Carlo sampling
Constructing Likelihoods, Priors and Posteriors
Density estimation and sample analysis
Gaussian process regression, optimisation and inversion
Approximate inference
Plotting and visualisation of inference results
inference-tools
Index
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Index
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A
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B
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C
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E
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G
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H
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I
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J
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L
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M
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O
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P
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R
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S
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T
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U
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W
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__call__() (inference.gp.GpRegressor method)
(inference.likelihoods.CauchyLikelihood method)
(inference.likelihoods.GaussianLikelihood method)
(inference.likelihoods.LogisticLikelihood method)
(inference.pdf.GaussianKDE method)
(inference.pdf.UnimodalPdf method)
(inference.posterior.Posterior method)
(inference.priors.ExponentialPrior method)
(inference.priors.GaussianPrior method)
(inference.priors.JointPrior method)
(inference.priors.UniformPrior method)
A
add_evaluation() (inference.gp.GpOptimiser method)
advance() (inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.ParallelTempering method)
(inference.mcmc.PcaChain method)
B
build_posterior() (inference.gp.GpRegressor method)
C
calculate_posterior() (inference.gp.GpLinearInverter method)
calculate_posterior_mean() (inference.gp.GpLinearInverter method)
CauchyLikelihood (class in inference.likelihoods)
ChangePoint (class in inference.gp)
conditional_sample() (in module inference.approx)
cost() (inference.posterior.Posterior method)
cost_gradient() (inference.posterior.Posterior method)
E
EnsembleSampler (class in inference.mcmc)
ExpectedImprovement (class in inference.gp)
ExponentialPrior (class in inference.priors)
G
GaussianKDE (class in inference.pdf)
GaussianLikelihood (class in inference.likelihoods)
GaussianPrior (class in inference.priors)
get_conditionals() (in module inference.approx)
get_interval() (inference.mcmc.GibbsChain method)
(inference.mcmc.PcaChain method)
get_marginal() (inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.PcaChain method)
get_parameter() (inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.PcaChain method)
get_probabilities() (inference.mcmc.EnsembleSampler method)
get_sample() (inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.PcaChain method)
GibbsChain (class in inference.mcmc)
GpLinearInverter (class in inference.gp)
GpOptimiser (class in inference.gp)
GpRegressor (class in inference.gp)
gradient() (inference.gp.GpRegressor method)
(inference.likelihoods.CauchyLikelihood method)
(inference.likelihoods.GaussianLikelihood method)
(inference.likelihoods.LogisticLikelihood method)
(inference.posterior.Posterior method)
(inference.priors.ExponentialPrior method)
(inference.priors.GaussianPrior method)
(inference.priors.JointPrior method)
(inference.priors.UniformPrior method)
H
HamiltonianChain (class in inference.mcmc)
hdi_plot() (in module inference.plotting)
HeteroscedasticNoise (class in inference.gp)
I
interval() (inference.pdf.GaussianKDE method)
J
JointPrior (class in inference.priors)
L
LogisticLikelihood (class in inference.likelihoods)
M
marginal_likelihood() (inference.gp.GpLinearInverter method)
matrix_plot() (in module inference.plotting)
(inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.PcaChain method)
mode (inference.pdf.GaussianKDE attribute)
mode() (inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.PcaChain method)
O
optimize_hyperparameters() (inference.gp.GpLinearInverter method)
P
ParallelTempering (class in inference.mcmc)
PcaChain (class in inference.mcmc)
plot_diagnostics() (inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.PcaChain method)
plot_summary() (inference.pdf.GaussianKDE method)
(inference.pdf.UnimodalPdf method)
Posterior (class in inference.posterior)
propose_evaluation() (inference.gp.GpOptimiser method)
R
RationalQuadratic (class in inference.gp)
return_chains() (inference.mcmc.ParallelTempering method)
run_for() (inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.ParallelTempering method)
(inference.mcmc.PcaChain method)
S
sample() (inference.priors.ExponentialPrior method)
(inference.priors.GaussianPrior method)
(inference.priors.JointPrior method)
(inference.priors.UniformPrior method)
sample_hdi() (in module inference.pdf)
set_boundaries() (inference.mcmc.GibbsChain method)
set_non_negative() (inference.mcmc.GibbsChain method)
shutdown() (inference.mcmc.ParallelTempering method)
SquaredExponential (class in inference.gp)
T
trace_plot() (in module inference.plotting)
(inference.mcmc.EnsembleSampler method)
(inference.mcmc.GibbsChain method)
(inference.mcmc.HamiltonianChain method)
(inference.mcmc.PcaChain method)
U
UniformPrior (class in inference.priors)
UnimodalPdf (class in inference.pdf)
UpperConfidenceBound (class in inference.gp)
W
WhiteNoise (class in inference.gp)
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