Package BIP :: Package Bayes :: Module like
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Module like

source code

Functions [hide private]
 
Categor(x, hist)
Categorical Log-likelihood generalization of a Bernoulli process for variables with any constant number of discrete values.
source code
 
Normal(x, mu, tau)
Normal Log-like
source code
 
Lognormal(x, mu, tau)
Lognormal Log-likelihood
source code
 
Poisson(x, mu)
Poisson Log-Likelihood function >>> Poisson([2],2) -1.30685281944
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Negbin(x, r, p)
Negative Binomial Log-Likelihood >>> Negbin([2,3],6,0.3) -9.16117424315
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Binomial(x, n, p)
Binomial Log-Likelihood >>> Binomial([2,3],6,0.3) -2.81280615454
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Weibull(x, alpha, beta)
Log-Like Weibull >>> Weibull([2,1,0.3,.5,1.7],1.5,3) -7.811955373
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Bernoulli(x, p)
Log-Like Bernoulli >>> Bernoulli([0,1,1,1,0,0,1,1],0.5) -5.54517744448
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Gamma(x, alpha, beta)
Log-Like Gamma >>> Gamma([2,3,7,6,4],2,2) -11.015748357
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Beta(x, a, b)
Log-Like Beta >>> Beta([.2,.3,.7,.6,.4],2,5) -0.434845728904
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Simple(x, w, a, start=0)
find out what it is.
source code
Function Details [hide private]

Categor(x, hist)

source code 

Categorical Log-likelihood generalization of a Bernoulli process for variables with any constant number of discrete values.

>>> Categor([1],([.3,.7],[0,1]))
-0.356674943939
Parameters:
  • x - data vector (list)
  • hist - tuple (prob,classes) classes contain the superior limit of the histogram classes

Normal(x, mu, tau)

source code 

Normal Log-like

>>> Normal([0],0,1)
-0.918938533205
Parameters:
  • mu - mean
  • tau - precision (1/sd)

Lognormal(x, mu, tau)

source code 

Lognormal Log-likelihood

>>> Lognormal([0.5,1,1.2],0,0.5)
-3.15728720569
Parameters:
  • mu - mean
  • tau - precision (1/sd)