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Everything about Bernoulli process

Random process of binary (boolean) random variables

In probability and statistics, a Bernoulli process is a finite or infinite sequence of binary random variables, so it is a discrete-time stochastic process that takes only two values, canonically 0 and 1. The component Bernoulli variables Xi are identically distributed and independent. Prosaically, a Bernoulli process is a repeated coin flipping, possibly with an unfair coin. Every variable Xi in the sequence is associated with a Bernoulli trial or experiment. They all have the same Bernoulli distribution. Much of what can be said about the Bernoulli process can also be generalized to more than two outcomes ; this generalization is known as the Bernoulli scheme. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Bernoulli processA 5-minute orientation
  2. Skim a recent paper: Student’s t-Based Robust Poisson Multi-Bernoulli Mixture Filter under Heavy-Tailed Process and Measurement NoisesInfluential work since 2022
  3. Pick up a classic book: Resolving Markov chains onto Bernoulli shifts via positive polynomialsThe most-reprinted book on the subject
  4. Read the landmark paper: Inference for a Bernoulli Process (a Bayesian View)Cited 110 times
  5. Go sideways: De Finetti's theoremA closely related topic
  6. Go sideways: Entropy (information theory)A closely related topic

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