sam/pyFTS
1
0
Fork 0
Code Issues 3 Pull Requests Actions Packages Projects Releases Wiki Activity

Updating the documentation of ProbabilityDistribution

Browse Source
This commit is contained in:
Petrônio Cândido de Lima e Silva 2018-10-01 15:42:17 -03:00 committed by GitHub
parent c42dea2aca
commit 971f79e621
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 9 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

14
pyFTS/probabilistic/ProbabilityDistribution.py
View File

@ -182,7 +182,8 @@ class ProbabilityDistribution(object):
def cumulative(self, values):
"""
Return the cumulative probability densities for the input values
Return the cumulative probability densities for the input values,
such that F(x) = P(X <= x)
:param values: A list of input values
:return: The cumulative probability densities for the input values
@ -201,7 +202,8 @@ class ProbabilityDistribution(object):
def quantile(self, values):
"""
Return the quantile values for the input values
Return the Universe of Discourse values in relation to the quantile input values,
such that Q(tau) = min( {x | F(x) >= tau })
:param values: input values
:return: The list of the quantile values for the input values
@ -222,7 +224,7 @@ class ProbabilityDistribution(object):
def entropy(self):
"""
Return the entropy of the probability distribution, H[X] =
Return the entropy of the probability distribution, H(P) = E[ -ln P(X) ] = - ∑ P(x) log ( P(x) )
:return:the entropy of the probability distribution
"""
@ -232,7 +234,8 @@ class ProbabilityDistribution(object):
def crossentropy(self,q):
"""
Cross entropy between the actual probability distribution and the informed one.
Cross entropy between the actual probability distribution and the informed one,
H(P,Q) = - ∑ P(x) log ( Q(x) )
:param q: a probabilistic.ProbabilityDistribution object
:return: Cross entropy between this probability distribution and the given distribution
@ -244,6 +247,7 @@ class ProbabilityDistribution(object):
def kullbackleiblerdivergence(self,q):
"""
Kullback-Leibler divergence between the actual probability distribution and the informed one.
DKL(P || Q) = - ∑ P(x) log( P(X) / Q(x) )
:param q: a probabilistic.ProbabilityDistribution object
:return: Kullback-Leibler divergence
@ -254,7 +258,7 @@ class ProbabilityDistribution(object):
def empiricalloglikelihood(self):
"""
Empirical Log Likelihood of the probability distribution
Empirical Log Likelihood of the probability distribution, L(P) = ∑ log( P(x) )
:return:
"""