add npm gaussian

gaussian/gaussian-tests.ts

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+const d = gaussian(0, 1);
+const _ = d.mean !== d.variance;
+const __ = d.mean * d.standardDeviation;
+d.pdf(-2);
+d.cdf(-1.28155);
+d.ppf(0.1);
+
+gaussian(0, 1).mul(gaussian(0, 1));
+gaussian(1, 1).mul(2);
+gaussian(1, 1).add(gaussian(1, 2));
+gaussian(1, 1).sub(gaussian(1, 2));
+gaussian(1, 1).div(gaussian(1, 2));
+gaussian(1, 1).div(2);
+gaussian(1, 1).scale(2);

gaussian/index.d.ts

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+// Type definitions for gaussian 1.1.0
+// Project: https://github.com/errcw/gaussian
+// Definitions by: Scott Cooper <https://github.com/scttcper>
+// Definitions: https://github.com/DefinitelyTyped/DefinitelyTyped
+
+declare function gaussian(mean: number, variance: number): gaussian.Gaussian;
+
+export = gaussian;
+export as namespace gaussian;
+
+declare namespace gaussian {
+	export interface Gaussian {
+		/**
+		 * the mean (μ) of the distribution
+		 */
+		mean: number;
+		/**
+		 * the variance (σ^2) of the distribution
+		 */
+		variance: number;
+		/**
+		 * the standard deviation (σ) of the distribution
+		 */
+		standardDeviation: number;
+		/**
+		 * the probability density function, which describes the
+		 * probability of a random variable taking on the value x
+		 */
+		pdf(x: number): number;
+		/**
+		 * the cumulative distribution function, which describes the
+		 * probability of a random variable falling in the interval (−∞, x]
+		 */
+		cdf(x: number): number;
+		/**
+		 * the percent point function, the inverse of cdf
+		 */
+		ppf(x: number): number;
+		/**
+		 * returns the product distribution of this and the given
+		 * distribution; equivalent to scale(d) when d is a constant
+		 */
+		mul(x: number | Gaussian): number;
+		/**
+		 * returns the quotient distribution of this and the given
+		 * distribution; equivalent to scale(1/d) when d is a constant
+		 */
+		div(x: number | Gaussian): number;
+		/**
+		 * returns the result of adding this and the given
+		 * distribution's means and variances
+		 */
+		add(x: Gaussian): number;
+		/**
+		 * returns the result of subtracting this and the given
+		 * distribution's means and variances
+		 */
+		sub(x: Gaussian): number;
+		/**
+		 * returns the result of scaling this distribution by the
+		 * given constant
+		 */
+		scale(x: number): number;
+	}
+}

gaussian/tsconfig.json

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+{
+    "compilerOptions": {
+        "module": "commonjs",
+        "target": "es6",
+        "noImplicitAny": true,
+        "strictNullChecks": true,
+        "baseUrl": "../",
+        "typeRoots": [
+            "../"
+        ],
+        "types": [],
+        "noEmit": true,
+        "forceConsistentCasingInFileNames": true
+    },
+    "files": [
+        "index.d.ts",
+        "gaussian-tests.ts"
+    ]
+}

gaussian/tslint.json

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+{ "extends": "../tslint.json" }