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alexey.radul.name | ||
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www.randomservices.org
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| | | | | [AI summary] The text presents a comprehensive overview of the beta-Bernoulli process and its related statistical properties. Key concepts include: 1) The Bayesian estimator of the probability parameter $ p $ based on Bernoulli trials, which is $ rac{a + Y_n}{a + b + n} $, where $ a $ and $ b $ are parameters of the beta distribution. 2) The stochastic process $ s{Z} = rac{a + Y_n}{a + b + n} $, which is a martingale and central to the theory of the beta-Bernoulli process. 3) The distribution of the trial number of the $ k $th success, $ V_k $, which follows a beta-negative binomial distribution. 4) The mean and variance of $ V_k $, derived using conditional expectations. 5) The connection between the beta distribution and the negative binomial distributi... | |
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statsandr.com
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| | | | | Learn how to run multiple and simple linear regression in R, how to interpret the results and how to verify the conditions of application | |
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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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teddykoker.com
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| | | In this post we will be using a method known as transfer learning in order to detect metastatic cancer in patches of images from digital pathology scans. | ||
