text: /**
  * @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.
  */
  
  /* eslint-disable no-restricted-syntax, no-invalid-this */
  
  'use strict';
  
  // MODULES //
  
  var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive;
  var defineProperty = require( '@stdlib/utils/define-property' );
  var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
  var setReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' );
  var kurtosis = require( '@stdlib/stats/base/dists/hypergeometric/kurtosis' );
  var mean = require( '@stdlib/stats/base/dists/hypergeometric/mean' );
  var mode = require( '@stdlib/stats/base/dists/hypergeometric/mode' );
  var skewness = require( '@stdlib/stats/base/dists/hypergeometric/skewness' );
  var stdev = require( '@stdlib/stats/base/dists/hypergeometric/stdev' );
  var variance = require( '@stdlib/stats/base/dists/hypergeometric/variance' );
  var cdf = require( '@stdlib/stats/base/dists/hypergeometric/cdf' );
  var logpmf = require( '@stdlib/stats/base/dists/hypergeometric/logpmf' );
  var pmf = require( '@stdlib/stats/base/dists/hypergeometric/pmf' );
  var quantile = require( '@stdlib/stats/base/dists/hypergeometric/quantile' );
  
  
  // FUNCTIONS //
  
  /**
  * Evaluates the cumulative distribution function (CDF).
  *
  * @private
  * @param {number} x - input value
  * @returns {Probability} evaluated CDF
  */
  function hypergeometricCDF( x ) {
  	return cdf( x, this.N, this.K, this.n );
  }
  
  /**
  * Evaluates the natural logarithm of the probability mass function (PMF).
  *
  * @private
  * @param {number} x - input value
  * @returns {Probability} evaluated PMF
  */
  function hypergeometricLogPMF( x ) {
  	return logpmf( x, this.N, this.K, this.n );
  }
  
  /**
  * Evaluates the probability mass function (PMF).
  *
  * @private
  * @param {number} x - input value
  * @returns {Probability} evaluated PMF
  */
  function hypergeometricPMF( x ) {
  	return pmf( x, this.N, this.K, this.n );
  }
  
  /**
  * Evaluates the quantile function.
  *
  * @private
  * @param {Probability} p - input probability
  * @returns {NonNegativeInteger} evaluated quantile function
  */
  function hypergeometricQuantile( p ) {
  	return quantile( p, this.N, this.K, this.n );
  }
  
  
  // MAIN //
  
  /**
  * Hypergeometric distribution constructor.
  *
  * @constructor
  * @param {NonNegativeInteger} N - population size
  * @param {NonNegativeInteger} K - subpopulation size
  * @param {NonNegativeInteger} n - number of draws
  * @throws {TypeError} `N` must be a non-negative integer
  * @throws {TypeError} `K` must be a non-negative integer
  * @throws {TypeError} `n` must be a non-negative integer
  * @throws {RangeError} `K` must not exceed `N`
  * @throws {RangeError} `n` must not exceed `N`
  * @returns {Hypergeometric} distribution instance
  *
  * @example
  * var hypergeometric = new Hypergeometric( 10, 5, 7 );
  *
  * var y = hypergeometric.cdf( 0.8 );
  * // returns 0.0
  *
  * var v = hypergeometric.mode;
  * // returns 4.0
  */
  function Hypergeometric( N, K, n ) {
  	if ( !(this instanceof Hypergeometric) ) {
  		return new Hypergeometric( N, K, n );
  	}
  	if ( !isNonNegativeInteger( N ) ) {
  		throw new TypeError( 'invalid argument. Population size `N` must be a non-negative integer. Value: `' + N + '`' );
  	}
  	if ( !isNonNegativeInteger( K ) ) {
  		throw new TypeError( 'invalid argument. Subpopulation size `K` must be a non-negative integer. Value: `' + K + '`' );
  	}
  	if ( !isNonNegativeInteger( n ) ) {
  		throw new TypeError( 'invalid argument. Number of draws `n` must be a non-negative integer. Value: `' + n + '`' );
  	}
  	if ( K > N ) {
  		throw new RangeError( 'invalid arguments. Subpopulation size `K` must be smaller than or equal to `N`.' );
  	}
  	if ( n > N ) {
  		throw new RangeError( 'invalid arguments. Number of draws `n` must be smaller than or equal to `N`.' );
  	}
  	defineProperty( this, 'N', {
  		'configurable': false,
  		'enumerable': true,
  		'get': function get() {
  			return N;
  		},
  		'set': function set( value ) {
  			if ( !isNonNegativeInteger( value ) ) {
  				throw new TypeError( 'invalid value. Must be a non-negative integer. Value: `' + value + '`' );
  			}
  			if ( K > value ) {
  				throw new RangeError( 'invalid value. Must be larger than or equal to `K`. Value: `' + value + '`' );
  			}
  			if ( n > value ) {
  				throw new RangeError( 'invalid value. Must be larger than or equal to `n`. Value: `' + value + '`' );
  			}
  			N = value;
  		}
  	});
  	defineProperty( this, 'K', {
  		'configurable': false,
  		'enumerable': true,
  		'get': function get() {
  			return K;
  		},
  		'set': function set( value ) {
  			if ( !isNonNegativeInteger( value ) ) {
  				throw new TypeError( 'invalid value. Must be a non-negative integer. Value: `' + value + '`' );
  			}
  			if ( value > N ) {
  				throw new RangeError( 'invalid value. Must be smaller than or equal to `N`. Value: `' + value + '`' );
  			}
  			K = value;
  		}
  	});
  	defineProperty( this, 'n', {
  		'configurable': false,
  		'enumerable': true,
  		'get': function get() {
  			return n;
  		},
  		'set': function set( value ) {
  			if ( !isNonNegativeInteger( value ) ) {
  				throw new TypeError( 'invalid value. Must be a non-negative integer. Value: `' + value + '`' );
  			}
  			if ( value > N ) {
  				throw new RangeError( 'invalid value. Must be smaller than or equal to `N`. Value: `' + value + '`' );
  			}
  			n = value;
  		}
  	});
  	return this;
  }
  
  /**
  * Hypergeometric distribution excess kurtosis.
  *
  * @name kurtosis
  * @memberof Hypergeometric.prototype
  * @type {number}
  * @see [kurtosis]{@link https://en.wikipedia.org/wiki/Kurtosis}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.kurtosis;
  * // returns ~-0.276
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'kurtosis', function get() {
  	return kurtosis( this.N, this.K, this.n );
  });
  
  /**
  * Hypergeometric distribution expected value.
  *
  * @name mean
  * @memberof Hypergeometric.prototype
  * @type {number}
  * @see [expected value]{@link https://en.wikipedia.org/wiki/Expected_value}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.mean;
  * // returns 3.75
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'mean', function get() {
  	return mean( this.N, this.K, this.n );
  });
  
  /**
  * Hypergeometric distribution mode.
  *
  * @name mode
  * @memberof Hypergeometric.prototype
  * @type {NonNegativeInteger}
  * @see [mode]{@link https://en.wikipedia.org/wiki/Mode_%28statistics%29}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.mode;
  * // returns 4.0
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'mode', function get() {
  	return mode( this.N, this.K, this.n );
  });
  
  /**
  * Hypergeometric distribution skewness.
  *
  * @name skewness
  * @memberof Hypergeometric.prototype
  * @type {number}
  * @see [skewness]{@link https://en.wikipedia.org/wiki/Skewness}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.skewness;
  * // returns ~-0.323
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'skewness', function get() {
  	return skewness( this.N, this.K, this.n );
  });
  
  /**
  * Hypergeometric distribution standard deviation.
  *
  * @name stdev
  * @memberof Hypergeometric.prototype
  * @type {NonNegativeNumber}
  * @see [standard deviation]{@link https://en.wikipedia.org/wiki/Standard_deviation}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.stdev;
  * // returns ~0.86
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'stdev', function get() {
  	return stdev( this.N, this.K, this.n );
  });
  
  /**
  * Hypergeometric distribution variance.
  *
  * @name variance
  * @memberof Hypergeometric.prototype
  * @type {NonNegativeNumber}
  * @see [variance]{@link https://en.wikipedia.org/wiki/Variance}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 20, 15, 5 );
  *
  * var v = hypergeometric.variance;
  * // returns ~0.74
  */
  setReadOnlyAccessor( Hypergeometric.prototype, 'variance', function get() {
  	return variance( this.N, this.K, this.n );
  });
  
  /**
  * Evaluates the cumulative distribution function (CDF).
  *
  * @name cdf
  * @memberof Hypergeometric.prototype
  * @type {Function}
  * @param {number} x - input value
  * @returns {Probability} evaluated CDF
  * @see [cdf]{@link https://en.wikipedia.org/wiki/Cumulative_distribution_function}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 8, 2, 4 );
  *
  * var v = hypergeometric.cdf( 0.5 );
  * // returns ~0.214
  */
  setReadOnly( Hypergeometric.prototype, 'cdf', hypergeometricCDF );
  
  /**
  * Evaluates the natural logarithm of the probability density function (PMF).
  *
  * @name logpmf
  * @memberof Hypergeometric.prototype
  * @type {Function}
  * @param {number} x - input value
  * @returns {number} evaluated logPMF
  * @see [pmf]{@link https://en.wikipedia.org/wiki/Probability_mass_function}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 8, 2, 4 );
  *
  * var v = hypergeometric.logpmf( 2.0 );
  * // returns ~-1.54
  */
  setReadOnly( Hypergeometric.prototype, 'logpmf', hypergeometricLogPMF );
  
  /**
  * Evaluates the probability density function (PMF).
  *
  * @name pmf
  * @memberof Hypergeometric.prototype
  * @type {Function}
  * @param {number} x - input value
  * @returns {number} evaluated PMF
  * @see [pmf]{@link https://en.wikipedia.org/wiki/Probability_mass_function}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 8, 2, 4 );
  *
  * var v = hypergeometric.pmf( 2.0 );
  * // returns ~0.214
  */
  setReadOnly( Hypergeometric.prototype, 'pmf', hypergeometricPMF );
  
  /**
  * Evaluates the quantile function.
  *
  * @name quantile
  * @memberof Hypergeometric.prototype
  * @type {Function}
  * @param {Probability} p - input probability
  * @returns {NonNegativeInteger} evaluated quantile function
  * @see [quantile function]{@link https://en.wikipedia.org/wiki/Quantile_function}
  *
  * @example
  * var hypergeometric = new Hypergeometric( 8, 2, 4 );
  *
  * var v = hypergeometric.quantile( 0.8 );
  * // returns 2.0
  */
  setReadOnly( Hypergeometric.prototype, 'quantile', hypergeometricQuantile );
  
  
  // EXPORTS //
  
  module.exports = Hypergeometric;
  