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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/lib/python3.9/site-packages/scipy/stats/__init__.py

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"""
.. _statsrefmanual:
==========================================
Statistical functions (:mod:`scipy.stats`)
==========================================
.. currentmodule:: scipy.stats
This module contains a large number of probability distributions as
well as a growing library of statistical functions.
Each univariate distribution is an instance of a subclass of `rv_continuous`
(`rv_discrete` for discrete distributions):
.. autosummary::
:toctree: generated/
rv_continuous
rv_discrete
rv_histogram
Continuous distributions
========================
.. autosummary::
:toctree: generated/
alpha -- Alpha
anglit -- Anglit
arcsine -- Arcsine
argus -- Argus
beta -- Beta
betaprime -- Beta Prime
bradford -- Bradford
burr -- Burr (Type III)
burr12 -- Burr (Type XII)
cauchy -- Cauchy
chi -- Chi
chi2 -- Chi-squared
cosine -- Cosine
crystalball -- Crystalball
dgamma -- Double Gamma
dweibull -- Double Weibull
erlang -- Erlang
expon -- Exponential
exponnorm -- Exponentially Modified Normal
exponweib -- Exponentiated Weibull
exponpow -- Exponential Power
f -- F (Snecdor F)
fatiguelife -- Fatigue Life (Birnbaum-Saunders)
fisk -- Fisk
foldcauchy -- Folded Cauchy
foldnorm -- Folded Normal
frechet_r -- Deprecated. Alias for weibull_min
frechet_l -- Deprecated. Alias for weibull_max
genlogistic -- Generalized Logistic
gennorm -- Generalized normal
genpareto -- Generalized Pareto
genexpon -- Generalized Exponential
genextreme -- Generalized Extreme Value
gausshyper -- Gauss Hypergeometric
gamma -- Gamma
gengamma -- Generalized gamma
genhalflogistic -- Generalized Half Logistic
geninvgauss -- Generalized Inverse Gaussian
gilbrat -- Gilbrat
gompertz -- Gompertz (Truncated Gumbel)
gumbel_r -- Right Sided Gumbel, Log-Weibull, Fisher-Tippett, Extreme Value Type I
gumbel_l -- Left Sided Gumbel, etc.
halfcauchy -- Half Cauchy
halflogistic -- Half Logistic
halfnorm -- Half Normal
halfgennorm -- Generalized Half Normal
hypsecant -- Hyperbolic Secant
invgamma -- Inverse Gamma
invgauss -- Inverse Gaussian
invweibull -- Inverse Weibull
johnsonsb -- Johnson SB
johnsonsu -- Johnson SU
kappa4 -- Kappa 4 parameter
kappa3 -- Kappa 3 parameter
ksone -- Distribution of Kolmogorov-Smirnov one-sided test statistic
kstwo -- Distribution of Kolmogorov-Smirnov two-sided test statistic
kstwobign -- Limiting Distribution of scaled Kolmogorov-Smirnov two-sided test statistic.
laplace -- Laplace
levy -- Levy
levy_l
levy_stable
logistic -- Logistic
loggamma -- Log-Gamma
loglaplace -- Log-Laplace (Log Double Exponential)
lognorm -- Log-Normal
loguniform -- Log-Uniform
lomax -- Lomax (Pareto of the second kind)
maxwell -- Maxwell
mielke -- Mielke's Beta-Kappa
moyal -- Moyal
nakagami -- Nakagami
ncx2 -- Non-central chi-squared
ncf -- Non-central F
nct -- Non-central Student's T
norm -- Normal (Gaussian)
norminvgauss -- Normal Inverse Gaussian
pareto -- Pareto
pearson3 -- Pearson type III
powerlaw -- Power-function
powerlognorm -- Power log normal
powernorm -- Power normal
rdist -- R-distribution
rayleigh -- Rayleigh
rice -- Rice
recipinvgauss -- Reciprocal Inverse Gaussian
semicircular -- Semicircular
skewnorm -- Skew normal
t -- Student's T
trapz -- Trapezoidal
triang -- Triangular
truncexpon -- Truncated Exponential
truncnorm -- Truncated Normal
tukeylambda -- Tukey-Lambda
uniform -- Uniform
vonmises -- Von-Mises (Circular)
vonmises_line -- Von-Mises (Line)
wald -- Wald
weibull_min -- Minimum Weibull (see Frechet)
weibull_max -- Maximum Weibull (see Frechet)
wrapcauchy -- Wrapped Cauchy
Multivariate distributions
==========================
.. autosummary::
:toctree: generated/
multivariate_normal -- Multivariate normal distribution
matrix_normal -- Matrix normal distribution
dirichlet -- Dirichlet
wishart -- Wishart
invwishart -- Inverse Wishart
multinomial -- Multinomial distribution
special_ortho_group -- SO(N) group
ortho_group -- O(N) group
unitary_group -- U(N) group
random_correlation -- random correlation matrices
Discrete distributions
======================
.. autosummary::
:toctree: generated/
bernoulli -- Bernoulli
betabinom -- Beta-Binomial
binom -- Binomial
boltzmann -- Boltzmann (Truncated Discrete Exponential)
dlaplace -- Discrete Laplacian
geom -- Geometric
hypergeom -- Hypergeometric
logser -- Logarithmic (Log-Series, Series)
nbinom -- Negative Binomial
planck -- Planck (Discrete Exponential)
poisson -- Poisson
randint -- Discrete Uniform
skellam -- Skellam
zipf -- Zipf
yulesimon -- Yule-Simon
An overview of statistical functions is given below.
Several of these functions have a similar version in
`scipy.stats.mstats` which work for masked arrays.
Summary statistics
==================
.. autosummary::
:toctree: generated/
describe -- Descriptive statistics
gmean -- Geometric mean
hmean -- Harmonic mean
kurtosis -- Fisher or Pearson kurtosis
mode -- Modal value
moment -- Central moment
skew -- Skewness
kstat --
kstatvar --
tmean -- Truncated arithmetic mean
tvar -- Truncated variance
tmin --
tmax --
tstd --
tsem --
variation -- Coefficient of variation
find_repeats
trim_mean
gstd -- Geometric Standard Deviation
iqr
sem
bayes_mvs
mvsdist
entropy
median_absolute_deviation
median_abs_deviation
Frequency statistics
====================
.. autosummary::
:toctree: generated/
cumfreq
itemfreq
percentileofscore
scoreatpercentile
relfreq
.. autosummary::
:toctree: generated/
binned_statistic -- Compute a binned statistic for a set of data.
binned_statistic_2d -- Compute a 2-D binned statistic for a set of data.
binned_statistic_dd -- Compute a d-D binned statistic for a set of data.
Correlation functions
=====================
.. autosummary::
:toctree: generated/
f_oneway
pearsonr
spearmanr
pointbiserialr
kendalltau
weightedtau
linregress
siegelslopes
theilslopes
multiscale_graphcorr
Statistical tests
=================
.. autosummary::
:toctree: generated/
ttest_1samp
ttest_ind
ttest_ind_from_stats
ttest_rel
chisquare
power_divergence
kstest
ks_1samp
ks_2samp
epps_singleton_2samp
mannwhitneyu
tiecorrect
rankdata
ranksums
wilcoxon
kruskal
friedmanchisquare
brunnermunzel
combine_pvalues
jarque_bera
.. autosummary::
:toctree: generated/
ansari
bartlett
levene
shapiro
anderson
anderson_ksamp
binom_test
fligner
median_test
mood
skewtest
kurtosistest
normaltest
Transformations
===============
.. autosummary::
:toctree: generated/
boxcox
boxcox_normmax
boxcox_llf
yeojohnson
yeojohnson_normmax
yeojohnson_llf
obrientransform
sigmaclip
trimboth
trim1
zmap
zscore
Statistical distances
=====================
.. autosummary::
:toctree: generated/
wasserstein_distance
energy_distance
Random variate generation
=========================
.. autosummary::
:toctree: generated/
rvs_ratio_uniforms
Circular statistical functions
==============================
.. autosummary::
:toctree: generated/
circmean
circvar
circstd
Contingency table functions
===========================
.. autosummary::
:toctree: generated/
chi2_contingency
contingency.expected_freq
contingency.margins
fisher_exact
Plot-tests
==========
.. autosummary::
:toctree: generated/
ppcc_max
ppcc_plot
probplot
boxcox_normplot
yeojohnson_normplot
Masked statistics functions
===========================
.. toctree::
stats.mstats
Univariate and multivariate kernel density estimation
=====================================================
.. autosummary::
:toctree: generated/
gaussian_kde
Warnings used in :mod:`scipy.stats`
===================================
.. autosummary::
:toctree: generated/
F_onewayConstantInputWarning
F_onewayBadInputSizesWarning
PearsonRConstantInputWarning
PearsonRNearConstantInputWarning
SpearmanRConstantInputWarning
For many more stat related functions install the software R and the
interface package rpy.
"""
from .stats import *
from .distributions import *
from .morestats import *
from ._binned_statistic import *
from .kde import gaussian_kde
from . import mstats
from .contingency import chi2_contingency
from ._multivariate import *
__all__ = [s for s in dir() if not s.startswith("_")] # Remove dunders.
from scipy._lib._testutils import PytestTester
test = PytestTester(__name__)
del PytestTester