123456789101112131415161718192021222324252627282930313233343536373839404142434445464748
import epsilon from "./epsilon.js";
/** * The [Poisson Distribution](http://en.wikipedia.org/wiki/Poisson_distribution) * is a discrete probability distribution that expresses the probability * of a given number of events occurring in a fixed interval of time * and/or space if these events occur with a known average rate and * independently of the time since the last event. * * The Poisson Distribution is characterized by the strictly positive * mean arrival or occurrence rate, `λ`. * * @param {number} lambda location poisson distribution * @returns {number[]} values of poisson distribution at that point */function poissonDistribution(lambda) /*: ?number[] */ {    // Check that lambda is strictly positive    if (lambda <= 0) {        return undefined;    }
    // our current place in the distribution    let x = 0;    // and we keep track of the current cumulative probability, in    // order to know when to stop calculating chances.    let cumulativeProbability = 0;    // the calculated cells to be returned    const cells = [];    let factorialX = 1;
    // This algorithm iterates through each potential outcome,    // until the `cumulativeProbability` is very close to 1, at    // which point we've defined the vast majority of outcomes    do {        // a [probability mass function](https://en.wikipedia.org/wiki/Probability_mass_function)        cells[x] = (Math.exp(-lambda) * Math.pow(lambda, x)) / factorialX;        cumulativeProbability += cells[x];        x++;        factorialX *= x;        // when the cumulativeProbability is nearly 1, we've calculated        // the useful range of this distribution    } while (cumulativeProbability < 1 - epsilon);
    return cells;}
export default poissonDistribution;