Index

A

a (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic attribute) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian attribute) alpha (normix.distributions.gamma.Gamma attribute) (normix.distributions.inverse_gamma.InverseGamma attribute) (normix.distributions.normal_inverse_gamma.FactorNormalInverseGamma property) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma attribute) (normix.distributions.normal_inverse_gamma.NormalInverseGamma property) (normix.distributions.variance_gamma.FactorVarianceGamma property) (normix.distributions.variance_gamma.JointVarianceGamma attribute) (normix.distributions.variance_gamma.VarianceGamma property)

B

b (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic attribute) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian attribute) BatchEMFitter (class in normix.fitting.em) beta (normix.distributions.gamma.Gamma attribute) (normix.distributions.inverse_gamma.InverseGamma attribute) (normix.distributions.normal_inverse_gamma.FactorNormalInverseGamma property) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma attribute) (normix.distributions.normal_inverse_gamma.NormalInverseGamma property) (normix.distributions.variance_gamma.FactorVarianceGamma property) (normix.distributions.variance_gamma.JointVarianceGamma attribute) (normix.distributions.variance_gamma.VarianceGamma property)

bregman_divergence() (normix.exponential_family.ExponentialFamily class method) bregman_objective() (in module normix.fitting.solvers) BregmanResult (class in normix.fitting.solvers)

C

cdf() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) (normix.exponential_family.ExponentialFamily method) compute_eta_from_model() (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method)

conditional_expectations() (normix.mixtures.joint.JointNormalMixture method) converged (normix.fitting.em.EMResult attribute) (normix.fitting.solvers.BregmanResult attribute) cov() (normix.distributions.normal.MultivariateNormal method) (normix.mixtures.marginal.NormalMixture method)

D

d (normix.distributions.normal.MultivariateNormal property) (normix.mixtures.joint.JointNormalMixture property) (normix.mixtures.marginal.NormalMixture property) default_init() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic class method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic class method) (normix.exponential_family.ExponentialFamily class method) (normix.mixtures.marginal.NormalMixture class method)

dim (normix.distributions.normal.MultivariateNormal property) diverged (normix.fitting.em.EMResult attribute)

E

e_step() (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method) elapsed_time (normix.fitting.em.EMResult attribute) (normix.fitting.solvers.BregmanResult attribute) em_convergence_params() (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method)

EMResult (class in normix.fitting.em) expectation_params() (normix.exponential_family.ExponentialFamily method) expectation_params_batch() (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian static method) ExponentialFamily (class in normix.exponential_family)

F

FactorGeneralizedHyperbolic (class in normix.distributions.generalized_hyperbolic) FactorNormalInverseGamma (class in normix.distributions.normal_inverse_gamma) FactorNormalInverseGaussian (class in normix.distributions.normal_inverse_gaussian) FactorVarianceGamma (class in normix.distributions.variance_gamma) fisher_information() (normix.exponential_family.ExponentialFamily method) fit() (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) (normix.distributions.normal_inverse_gamma.NormalInverseGamma method) (normix.distributions.variance_gamma.VarianceGamma method) (normix.exponential_family.ExponentialFamily method) (normix.fitting.em.BatchEMFitter method) (normix.fitting.em.IncrementalEMFitter method) (normix.mixtures.marginal.MarginalMixture method) fit_mle() (normix.exponential_family.ExponentialFamily class method) from_classical() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic class method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic class method) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic class method) (normix.distributions.generalized_hyperbolic.UnivariateGeneralizedHyperbolic class method) (normix.distributions.normal.MultivariateNormal class method) (normix.distributions.normal_inverse_gamma.FactorNormalInverseGamma class method) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma class method) (normix.distributions.normal_inverse_gamma.NormalInverseGamma class method) (normix.distributions.normal_inverse_gamma.UnivariateNormalInverseGamma class method) (normix.distributions.normal_inverse_gaussian.FactorNormalInverseGaussian class method) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian class method) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian class method) (normix.distributions.normal_inverse_gaussian.UnivariateNormalInverseGaussian class method) (normix.distributions.variance_gamma.FactorVarianceGamma class method) (normix.distributions.variance_gamma.JointVarianceGamma class method) (normix.distributions.variance_gamma.UnivariateVarianceGamma class method) (normix.distributions.variance_gamma.VarianceGamma class method)

from_expectation() (normix.distributions.gamma.Gamma class method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian class method) (normix.distributions.inverse_gamma.InverseGamma class method) (normix.distributions.inverse_gaussian.InverseGaussian class method) (normix.distributions.normal.MultivariateNormal class method) (normix.exponential_family.ExponentialFamily class method) (normix.mixtures.joint.JointNormalMixture class method) (normix.mixtures.marginal.NormalMixture class method) from_natural() (normix.distributions.gamma.Gamma class method) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic class method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian class method) (normix.distributions.inverse_gamma.InverseGamma class method) (normix.distributions.inverse_gaussian.InverseGaussian class method) (normix.distributions.normal.MultivariateNormal class method) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma class method) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian class method) (normix.distributions.variance_gamma.JointVarianceGamma class method) (normix.exponential_family.ExponentialFamily class method) fun (normix.fitting.solvers.BregmanResult attribute)

G

Gamma (class in normix.distributions.gamma) gamma (normix.mixtures.joint.JointNormalMixture attribute) (normix.mixtures.marginal.NormalMixture property)

GeneralizedHyperbolic (class in normix.distributions.generalized_hyperbolic) GeneralizedInverseGaussian (class in normix.distributions.generalized_inverse_gaussian) GIG (in module normix.distributions.generalized_inverse_gaussian) grad_norm (normix.fitting.solvers.BregmanResult attribute)

I

IncrementalEMFitter (class in normix.fitting.em)

InverseGamma (class in normix.distributions.inverse_gamma) InverseGaussian (class in normix.distributions.inverse_gaussian)

J

joint (normix.mixtures.marginal.NormalMixture property) JointGeneralizedHyperbolic (class in normix.distributions.generalized_hyperbolic) JointNormalInverseGamma (class in normix.distributions.normal_inverse_gamma)

JointNormalInverseGaussian (class in normix.distributions.normal_inverse_gaussian) JointNormalMixture (class in normix.mixtures.joint) JointVarianceGamma (class in normix.distributions.variance_gamma)

K

kl_divergence() (normix.exponential_family.ExponentialFamily method) (normix.mixtures.marginal.NormalMixture method)

L

L_Sigma (normix.distributions.normal.MultivariateNormal attribute) (normix.mixtures.joint.JointNormalMixture attribute) (normix.mixtures.marginal.NormalMixture property) lam (normix.distributions.inverse_gaussian.InverseGaussian attribute) (normix.distributions.normal_inverse_gaussian.FactorNormalInverseGaussian property) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian attribute) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian property) log_base_measure() (normix.distributions.gamma.Gamma static method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian static method) (normix.distributions.inverse_gamma.InverseGamma static method) (normix.distributions.inverse_gaussian.InverseGaussian static method) (normix.distributions.normal.MultivariateNormal static method) (normix.exponential_family.ExponentialFamily static method) (normix.mixtures.joint.JointNormalMixture static method) log_det_sigma() (normix.mixtures.joint.JointNormalMixture method) (normix.mixtures.marginal.NormalMixture method)

log_kv() (in module normix.utils.bessel) log_likelihoods (normix.fitting.em.EMResult attribute) log_partition() (normix.exponential_family.ExponentialFamily method) log_prob() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) (normix.distributions.normal.MultivariateNormal method) (normix.distributions.normal_inverse_gamma.FactorNormalInverseGamma method) (normix.distributions.normal_inverse_gamma.NormalInverseGamma method) (normix.distributions.normal_inverse_gaussian.FactorNormalInverseGaussian method) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian method) (normix.distributions.variance_gamma.FactorVarianceGamma method) (normix.distributions.variance_gamma.VarianceGamma method) (normix.exponential_family.ExponentialFamily method) (normix.mixtures.marginal.MarginalMixture method) log_prob_joint() (normix.mixtures.joint.JointNormalMixture method)

M

m_step() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method) m_step_normal() (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method) m_step_subordinator() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) (normix.mixtures.marginal.MarginalMixture method) (normix.mixtures.marginal.NormalMixture method) make_jit_newton_solver() (in module normix.fitting.solvers) marginal_log_likelihood() (normix.mixtures.marginal.MarginalMixture method) MarginalMixture (class in normix.mixtures.marginal) mean() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) (normix.distributions.normal.MultivariateNormal method) (normix.exponential_family.ExponentialFamily method) (normix.mixtures.marginal.NormalMixture method) mode() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) model (normix.fitting.em.EMResult attribute)

module normix.distributions.gamma normix.distributions.generalized_hyperbolic normix.distributions.generalized_inverse_gaussian normix.distributions.inverse_gamma normix.distributions.inverse_gaussian normix.distributions.normal normix.distributions.normal_inverse_gamma normix.distributions.normal_inverse_gaussian normix.distributions.variance_gamma normix.exponential_family normix.fitting.em normix.fitting.solvers normix.mixtures.joint normix.mixtures.marginal normix.utils.bessel normix.utils.constants mu (normix.distributions.inverse_gaussian.InverseGaussian attribute) (normix.distributions.normal.MultivariateNormal attribute) (normix.mixtures.joint.JointNormalMixture attribute) (normix.mixtures.marginal.NormalMixture property) mu_ig (normix.distributions.normal_inverse_gaussian.FactorNormalInverseGaussian property) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian attribute) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian property) MultivariateNormal (class in normix.distributions.normal)

N

n_iter (normix.fitting.em.EMResult attribute) natural_params() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) (normix.distributions.normal.MultivariateNormal method) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma method) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian method) (normix.distributions.variance_gamma.JointVarianceGamma method) (normix.exponential_family.ExponentialFamily method) NormalInverseGamma (class in normix.distributions.normal_inverse_gamma) NormalInverseGaussian (class in normix.distributions.normal_inverse_gaussian) NormalMixture (class in normix.mixtures.marginal) normix.distributions.gamma module normix.distributions.generalized_hyperbolic module normix.distributions.generalized_inverse_gaussian module normix.distributions.inverse_gamma module normix.distributions.inverse_gaussian module

normix.distributions.normal module normix.distributions.normal_inverse_gamma module normix.distributions.normal_inverse_gaussian module normix.distributions.variance_gamma module normix.exponential_family module normix.fitting.em module normix.fitting.solvers module normix.mixtures.joint module normix.mixtures.marginal module normix.utils.bessel module normix.utils.constants module num_steps (normix.fitting.solvers.BregmanResult attribute)

P

p (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic property) (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic attribute) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian attribute) param_changes (normix.fitting.em.EMResult attribute) pdf() (normix.exponential_family.ExponentialFamily method) (normix.mixtures.marginal.MarginalMixture method)

ppf() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) project() (normix.mixtures.marginal.NormalMixture method)

R

regularize_a_eq_b() (normix.distributions.generalized_hyperbolic.FactorGeneralizedHyperbolic method) (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) (normix.distributions.normal_inverse_gaussian.FactorNormalInverseGaussian method) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian method) (normix.mixtures.marginal.NormalMixture method) regularize_det_sigma() (normix.mixtures.marginal.NormalMixture method) regularize_det_sigma_one() (normix.mixtures.marginal.NormalMixture method) replace() (normix.mixtures.marginal.NormalMixture method)

rvs() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) (normix.distributions.normal.MultivariateNormal method) (normix.exponential_family.ExponentialFamily method) (normix.mixtures.joint.JointNormalMixture method) (normix.mixtures.marginal.NormalMixture method)

S

sample() (normix.distributions.normal.MultivariateNormal method) sigma (normix.distributions.normal.MultivariateNormal property) sigma() (normix.mixtures.joint.JointNormalMixture method) (normix.mixtures.marginal.NormalMixture method) solve_bregman() (in module normix.fitting.solvers) solve_bregman_multistart() (in module normix.fitting.solvers) squared_hellinger() (normix.exponential_family.ExponentialFamily method) (normix.mixtures.marginal.NormalMixture method) std() (normix.exponential_family.ExponentialFamily method) subordinator() (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic method) (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma method) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian method) (normix.distributions.variance_gamma.JointVarianceGamma method) (normix.mixtures.joint.JointNormalMixture method)

sufficient_statistics() (normix.distributions.gamma.Gamma static method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian static method) (normix.distributions.inverse_gamma.InverseGamma static method) (normix.distributions.inverse_gaussian.InverseGaussian static method) (normix.distributions.normal.MultivariateNormal static method) (normix.exponential_family.ExponentialFamily static method) (normix.mixtures.joint.JointNormalMixture static method)

T

theta (normix.fitting.solvers.BregmanResult attribute) to_gamma() (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) to_generalized_hyperbolic() (normix.distributions.normal_inverse_gamma.NormalInverseGamma method) (normix.distributions.normal_inverse_gaussian.NormalInverseGaussian method) (normix.distributions.variance_gamma.VarianceGamma method) to_gig() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) to_inverse_gamma() (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method)

to_inverse_gaussian() (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) to_joint_generalized_hyperbolic() (normix.distributions.normal_inverse_gamma.JointNormalInverseGamma method) (normix.distributions.normal_inverse_gaussian.JointNormalInverseGaussian method) (normix.distributions.variance_gamma.JointVarianceGamma method) to_joint_normal_inverse_gamma() (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic method) to_joint_normal_inverse_gaussian() (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic method) to_joint_variance_gamma() (normix.distributions.generalized_hyperbolic.JointGeneralizedHyperbolic method) to_normal_inverse_gamma() (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) to_normal_inverse_gaussian() (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method) to_variance_gamma() (normix.distributions.generalized_hyperbolic.GeneralizedHyperbolic method)

U

UnivariateGeneralizedHyperbolic (class in normix.distributions.generalized_hyperbolic) UnivariateNormalInverseGamma (class in normix.distributions.normal_inverse_gamma)

UnivariateNormalInverseGaussian (class in normix.distributions.normal_inverse_gaussian) UnivariateVarianceGamma (class in normix.distributions.variance_gamma)

V

var() (normix.distributions.gamma.Gamma method) (normix.distributions.generalized_inverse_gaussian.GeneralizedInverseGaussian method) (normix.distributions.inverse_gamma.InverseGamma method) (normix.distributions.inverse_gaussian.InverseGaussian method) (normix.exponential_family.ExponentialFamily method)

VarianceGamma (class in normix.distributions.variance_gamma)