| 1 | /**
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| 2 | * The [Bernoulli distribution](http://en.wikipedia.org/wiki/Bernoulli_distribution)
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| 3 | * is the probability discrete
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| 4 | * distribution of a random variable which takes value 1 with success
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| 5 | * probability `p` and value 0 with failure
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| 6 | * probability `q` = 1 - `p`. It can be used, for example, to represent the
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| 7 | * toss of a coin, where "1" is defined to mean "heads" and "0" is defined
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| 8 | * to mean "tails" (or vice versa). It is
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| 9 | * a special case of a Binomial Distribution
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| 10 | * where `n` = 1.
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| 11 | *
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| 12 | * @param {number} p input value, between 0 and 1 inclusive
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| 13 | * @returns {number[]} values of bernoulli distribution at this point
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| 14 | * @throws {Error} if p is outside 0 and 1
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| 15 | * @example
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| 16 | * bernoulliDistribution(0.3); // => [0.7, 0.3]
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| 17 | */
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| 18 | function bernoulliDistribution(p) /*: number[] */ {
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| 19 | // Check that `p` is a valid probability (0 ≤ p ≤ 1)
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| 20 | if (p < 0 || p > 1) {
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| 21 | throw new Error(
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| 22 | "bernoulliDistribution requires probability to be between 0 and 1 inclusive"
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| 23 | );
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| 24 | }
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| 25 |
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| 26 | return [1 - p, p];
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| 27 | }
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| 28 |
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| 29 | export default bernoulliDistribution;
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