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dm13450.github.io | ||
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nelari.us
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| | | | | 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? | |
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www.huber.embl.de
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| | | | | If you are a biologist and want to get the best out of the powerful methods of modern computational statistics, this is your book. | |
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freerangestats.info
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| | | | | I look at some unusual data where the median was higher than the mode, and show how to model it in Stan as a mixture of two negative binomial distributions. | |
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p.migdal.pl
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| | | Academia to data science? Learn Python (or R), machine learning and other stuff. | ||
