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| | | | | nelari.us | |
| | | | | In inverse transform sampling, the inverse cumulative distribution function is used to generate random numbers in a given distribution. But why does this work? And how can you use it to generate random numbers in a given distribution by drawing random numbers from any arbitrary distribution? | |
| | | | | thirdorderscientist.org | |
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| | | | | sriku.org | |
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| | | | | darrenjw.wordpress.com | |
| | | Yesterday there was an RSS Read Paper meeting for the paper Unbiased Markov chain Monte Carlo with couplings by Pierre Jacob, John O'Leary and Yves F. Atchadé. The paper addresses the bias in MCMC estimates due to lack of convergence to equilibrium (the "burn-in" problem), and shows how it is possible to modify MCMC algorithms... | ||