/* This is a generated file. Do not edit directly. */

/* harmony default export */

/* harmony export (binding) */

/* harmony import */

/*#__PURE__*/

/**
	* Evaluates the cumulative distribution function (CDF) for an exponential distribution.
	*
	* @private
	* @param {number} x - input value
	* @returns {Probability} evaluated CDF
	*
	* @example
	* var y = cdf( 2.0 );
	* // returns <number>
	*/

/**
	* Evaluates the probability density function (PDF) for an exponential distribution.
	*
	* @private
	* @param {number} x - input value
	* @returns {number} evaluated PDF
	*
	* @example
	* var y = pdf( 2.3 );
	* // returns <number>
	*/

/**
	* Evaluates the quantile function for an exponential distribution.
	*
	* @private
	* @param {Probability} p - input value
	* @returns {number} evaluated quantile function
	*
	* @example
	* var y = quantile( 0.3 );
	* // returns <number>
	*/

/**
 * Iterates through children that are "valid elements".
 *
 * The provided forEachFunc(child, index) will be called for each
 * leaf child with the index reflecting the position relative to "valid components".
 */

/**
 * Iterates through children that are typically specified as `props.children`,
 * but only maps over children that are "valid elements".
 *
 * The mapFunction provided index will be normalised to the components mapped,
 * so an invalid component would not increase the index.
 *
 */

/**
* @license Apache-2.0
*
* Copyright (c) 2018 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*
* ## Notice
*
* The following copyright and license were part of the original implementation available as part of [FreeBSD]{@link https://svnweb.freebsd.org/base/release/9.3.0/lib/msun/src/e_log.c}. The implementation follows the original, but has been modified for JavaScript.
*
* ```text
* Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
*
* Developed at SunPro, a Sun Microsystems, Inc. business.
* Permission to use, copy, modify, and distribute this
* software is freely granted, provided that this notice
* is preserved.
* ```
*/

/**
* @license Apache-2.0
*
* Copyright (c) 2018 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

/**
* Evaluate the natural logarithm.
*
* @module @stdlib/math/base/special/ln
*
* @example
* var ln = require( '@stdlib/math/base/special/ln' );
*
* var v = ln( 4.0 );
* // returns ~1.386
*
* v = ln( 0.0 );
* // returns -Infinity
*
* v = ln( Infinity );
* // returns Infinity
*
* v = ln( NaN );
* // returns NaN
*
* v = ln( -4.0 );
* // returns NaN
*/

/**
* Evaluates a polynomial.
*
* ## Notes
*
* -   The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
*
* @private
* @param {number} x - value at which to evaluate the polynomial
* @returns {number} evaluated polynomial
*/

/**
* Evaluates the cumulative distribution function (CDF) for an exponential distribution with rate parameter `lambda` at a value `x`.
*
* @param {number} x - input value
* @param {PositiveNumber} lambda - rate parameter
* @returns {Probability} evaluated CDF
*
* @example
* var y = cdf( 2.0, 0.1 );
* // returns ~0.181
*
* @example
* var y = cdf( 1.0, 2.0 );
* // returns ~0.865
*
* @example
* var y = cdf( -1.0, 4.0 );
* // returns 0.0
*
* @example
* var y = cdf( NaN, 1.0 );
* // returns NaN
*
* @example
* var y = cdf( 0.0, NaN );
* // returns NaN
*
* @example
* // Negative rate parameter:
* var y = cdf( 2.0, -1.0 );
* // returns NaN
*/

/**
* Evaluates the natural logarithm.
*
* @param {NonNegativeNumber} x - input value
* @returns {number} function value
*
* @example
* var v = ln( 4.0 );
* // returns ~1.386
*
* @example
* var v = ln( 0.0 );
* // returns -Infinity
*
* @example
* var v = ln( Infinity );
* // returns Infinity
*
* @example
* var v = ln( NaN );
* // returns NaN
*
* @example
* var v = ln( -4.0 );
* // returns NaN
*/

/**
* Evaluates the probability density function (PDF) for an exponential distribution with rate parameter `lambda` at a value `x`.
*
* @param {number} x - input value
* @param {PositiveNumber} lambda - rate parameter
* @returns {number} evaluated PDF
*
* @example
* var y = pdf( 0.3, 4.0 );
* // returns ~1.205
*
* @example
* var y = pdf( 2.0, 0.7 );
* // returns ~0.173
*
* @example
* var y = pdf( -1.0, 0.5 );
* // returns 0.0
*
* @example
* var y = pdf( 0, NaN );
* // returns NaN
*
* @example
* var y = pdf( NaN, 2.0 );
* // returns NaN
*
* @example
* // Negative rate:
* var y = pdf( 2.0, -1.0 );
* // returns NaN
*/

/**
* Evaluates the quantile function for an exponential distribution with rate parameter `lambda` at a probability `p`.
*
* @param {Probability} p - input value
* @param {PositiveNumber} lambda - rate parameter
* @returns {number} evaluated quantile function
*
* @example
* var y = quantile( 0.8, 1.0 );
* // returns ~1.609
*
* @example
* var y = quantile( 0.5, 4.0 );
* // returns ~0.173
*
* @example
* var y = quantile( 0.5, 0.1 );
* // returns ~6.931
*
* @example
* var y = quantile( -0.2, 0.1 );
* // returns NaN
*
* @example
* var y = quantile( NaN, 1.0 );
* // returns NaN
*
* @example
* var y = quantile( 0.0, NaN );
* // returns NaN
*
* @example
* // Negative rate parameter:
* var y = quantile( 0.5, -1.0 );
* // returns NaN
*/

/**
* Exponential distribution cumulative distribution function (CDF).
*
* @module @stdlib/stats/base/dists/exponential/cdf
*
* @example
* var cdf = require( '@stdlib/stats/base/dists/exponential/cdf' );
*
* var y = cdf( 2.0, 0.1 );
* // returns ~0.181
*
* var myCDF = cdf.factory( 0.5 );
* y = myCDF( 3.0 );
* // returns ~0.777
*/

/**
* Exponential distribution probability density function (PDF).
*
* @module @stdlib/stats/base/dists/exponential/pdf
*
* @example
* var pdf = require( '@stdlib/stats/base/dists/exponential/pdf' );
*
* var y = pdf( 0.3, 4.0 );
* // returns ~1.205
*
* var myPDF = pdf.factory( 0.5 );
*
* y = myPDF( 3.0 );
* // returns ~0.112
*
* y = myPDF( 1.0 );
* // returns ~0.303
*/

/**
* Exponential distribution quantile function.
*
* @module @stdlib/stats/base/dists/exponential/quantile
*
* @example
* var quantile = require( '@stdlib/stats/base/dists/exponential/quantile' );
*
* var y = quantile( 0.5, 4.0 );
* // returns ~0.173
*
* var myQuantile = quantile.factory( 0.4 );
*
* y = myQuantile( 0.4 );
* // returns ~1.277
*
* y = myQuantile( 1.0 );
* // returns Infinity
*/

/**
* Returns a function for evaluating the cumulative distribution function (CDF) for an exponential distribution with rate parameter `lambda`.
*
* @param {PositiveNumber} lambda - rate parameter
* @returns {Function} CDF
*
* @example
* var cdf = factory( 0.5 );
* var y = cdf( 3.0 );
* // returns ~0.777
*
* y = cdf( 1.0 );
* // returns ~0.393
*/

/**
* Returns a function for evaluating the probability density function (PDF) for an exponential distribution with parameter `lambda`.
*
* @param {PositiveNumber} lambda - rate parameter
* @returns {Function} probability density function (PDF)
*
* @example
* var pdf = factory( 0.5 );
* var y = pdf( 3.0 );
* // returns ~0.112
*
* y = pdf( 1.0 );
* // returns ~0.303
*/

/**
* Returns a function for evaluating the quantile function of an exponential distribution with rate parameter `lambda`.
*
* @param {PositiveNumber} lambda - rate parameter
* @returns {Function} quantile function
*
* @example
* var quantile = factory( 0.4 );
* var y = quantile( 0.4 );
* // returns ~1.277
*
* y = quantile( 1.0 );
* // returns Infinity
*/

/***/

// Case: -2**-20 <= f < 2**-20

// Case: 0 < x < 2**-1022

// EXPORTS //

// MAIN //

// MODULES //

// Need to define the default "as" during prop destructuring to be compatible with styled-components github.com/react-bootstrap/react-bootstrap/issues/3595

// Normalize `x` or `x/2`...

// Subnormal number, scale up `x`:

// We provide an empty the TabContext so `<Nav>`s in `<TabPane>`s don't

// asm type annotation

// conflict with the top level one.
