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model_builder/Bayes/gibbs.py

 

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# -*- coding:iso8859-1 -*-

 

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#-----------------------------------------------------------------------------

 

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# Name:        gibbs.py

 

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# Purpose:     This simple routine implements a simple Gibbs sampler.

 

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#

 

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# Author:      Fl�vio Code�o Coelho

 

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#

 

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# Created:     2003/25/09

 

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# RCS-ID:      $Id: module1.py $

 

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# Copyright:   (c) 2003

 

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# Licence:     GPL

 

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# Acknowledgements:   Whatever

 

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#-----------------------------------------------------------------------------

 

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from math import *

 

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from RandomArray import *

 

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from matplotlib.pylab import * 

 

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n=10000

 

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rho=.99 #correlation

 

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#Means

 

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m1 = 10

 

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m2 = 20

 

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#Standar deviations

 

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s1 = 1

 

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s2 = 1

 

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#Initialize vectors

 

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x=zeros(n, Float)

 

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y=zeros(n, Float)

 

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sd=sqrt(1-rho**2)

 

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# the core of the method: sample recursively from two normal distributions

 

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# Tthe mean for the current sample, is updated at each step.

 

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for i in range(1,n):

 

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  x[i] = normal(m1+rho*(y[i-1]-m2)/s2,s1*sd)

 

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  y[i] = normal(m2+rho*(x[i-1]-m1)/s1,s2*sd)

 

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scatter(x,y,marker='d',c='r')

 

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title('Amostrador de Gibbs')

 

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xlabel('x')

 

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ylabel('y')

 

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grid()

 

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show()

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