python - Ignoring samples in Gibbs sampling - 


import random,math  def gibbs(n=50000,thin=1000):     x=0     y=0     print "iter  x  y"     in range(n):         j in range(thin):             x=random.gammavariate(3,1.0/(y*y+4))             y=random.gauss(1.0/(x+1),1.0/math.sqrt(2*x+2))         print i,x,y  gibbs()

the above python code gibbs sampling , following line confuses me.

for j in range(thin):

what significance of additional inner loop?

the reason seems introduction of thinning gibbs sampling. thinning used reduce effect of correlation between consecutive samples. gibbs sampling generates markov chain of samples , nearby samples correlated, while typically intention draw samples independent.

to achieve that, can use every m-th value, while ignoring intermediate values. in case m stored in variable thinning , taking every thinning value printed below loop.


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