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Installation\r\n> `npm install --save @types/gaussian`\r\n\r\n# Summary\r\nThis package contains type definitions for gaussian (https://github.com/errcw/gaussian).\r\n\r\n# Details\r\nFiles were exported from https://github.com/DefinitelyTyped/DefinitelyTyped/tree/master/types/gaussian.\r\n## [index.d.ts](https://github.com/DefinitelyTyped/DefinitelyTyped/tree/master/types/gaussian/index.d.ts)\r\n````ts\r\ndeclare function gaussian(mean: number, variance: number): gaussian.Gaussian;\n\nexport = gaussian;\nexport as namespace gaussian;\n\ndeclare namespace gaussian {\n    interface Gaussian {\n        /**\n         * the mean (μ) of the distribution\n         */\n        mean: number;\n        /**\n         * the variance (σ^2) of the distribution\n         */\n        variance: number;\n        /**\n         * the standard deviation (σ) of the distribution\n         */\n        standardDeviation: number;\n        /**\n         * the probability density function, which describes the\n         * probability of a random variable taking on the value x\n         */\n        pdf(x: number): number;\n        /**\n         * the cumulative distribution function, which describes the\n         * probability of a random variable falling in the interval (−∞, x]\n         */\n        cdf(x: number): number;\n        /**\n         * the percent point function, the inverse of cdf\n         */\n        ppf(x: number): number;\n        /**\n         * returns the product distribution of this and the given\n         * distribution; equivalent to scale(d) when d is a constant\n         */\n        mul(x: number | Gaussian): Gaussian;\n        /**\n         * returns the quotient distribution of this and the given\n         * distribution; equivalent to scale(1/d) when d is a constant\n         */\n        div(x: number | Gaussian): Gaussian;\n        /**\n         * returns the result of adding this and the given\n         * distribution's means and variances\n         */\n        add(x: Gaussian): Gaussian;\n        /**\n         * returns the result of subtracting this and the given\n         * distribution's means and variances\n         */\n        sub(x: Gaussian): Gaussian;\n        /**\n         * returns the result of scaling this distribution by the\n         * given constant\n         */\n        scale(x: number): Gaussian;\n        /**\n         * generates given number of samples of the distribution\n         */\n        random(x: number, randFn?: () => number): number[];\n    }\n}\n\r\n````\r\n\r\n### Additional Details\r\n * Last updated: Tue, 07 Nov 2023 03:09:37 GMT\r\n * Dependencies: none\r\n\r\n# Credits\r\nThese definitions were written by [Scott Cooper](https://github.com/scttcper).","users":{}}