text: 'use strict';
  
  // MODULES //
  
  var isNumber = require( 'validate.io-number-primitive' ),
  	isArrayLike = require( 'validate.io-array-like' ),
  	isTypedArrayLike = require( 'validate.io-typed-array-like' ),
  	isMatrixLike = require( 'validate.io-matrix-like' ),
  	ctors = require( 'compute-array-constructors' ),
  	matrix = require( 'dstructs-matrix' ),
  	validate = require( './validate.js' );
  
  
  // FUNCTIONS //
  
  var cdf1 = require( './number.js' ),
  	cdf2 = require( './array.js' ),
  	cdf3 = require( './accessor.js' ),
  	cdf4 = require( './deepset.js' ),
  	cdf5 = require( './matrix.js' ),
  	cdf6 = require( './typedarray.js' );
  
  
  // CDF //
  
  /**
  * FUNCTION: cdf( x[, opts] )
  *	Evaluates the cumulative distribution function (CDF) for a Inverse Gamma distribution.
  *
  * @param {Number|Number[]|Array|Int8Array|Uint8Array|Uint8ClampedArray|Int16Array|Uint16Array|Int32Array|Uint32Array|Float32Array|Float64Array|Matrix} x - input value
  * @param {Object} [opts] - function options
  * @param {Number} [opts.alpha=1] - shape parameter
  * @param {Number} [opts.beta=1] - scale parameter
  * @param {Boolean} [opts.copy=true] - boolean indicating if the function should return a new data structure
  * @param {Function} [opts.accessor] - accessor function for accessing array values
  * @param {String} [opts.path] - deep get/set key path
  * @param {String} [opts.sep="."] - deep get/set key path separator
  * @param {String} [opts.dtype="float64"] - output data type
  * @returns {Number|Number[]|Array|Int8Array|Uint8Array|Uint8ClampedArray|Int16Array|Uint16Array|Int32Array|Uint32Array|Float32Array|Float64Array|Matrix} evaluated CDF
  */
  function cdf( x, options ) {
  	/* jshint newcap:false */
  	var opts = {},
  		ctor,
  		err,
  		out,
  		dt,
  		d;
  
  	if ( arguments.length > 1 ) {
  		err = validate( opts, options );
  		if ( err ) {
  			throw err;
  		}
  	}
  	opts.alpha = typeof opts.alpha !== 'undefined' ? opts.alpha : 1;
  	opts.beta = typeof opts.beta !== 'undefined' ? opts.beta : 1;
  
  	if ( isNumber( x ) ) {
  		return cdf1( x, opts.alpha, opts.beta );
  	}
  	if ( isMatrixLike( x ) ) {
  		if ( opts.copy !== false ) {
  			dt = opts.dtype || 'float64';
  			ctor = ctors( dt );
  			if ( ctor === null ) {
  				throw new Error( 'cdf()::invalid option. Data type option does not have a corresponding array constructor. Option: `' + dt + '`.' );
  			}
  			// Create an output matrix:
  			d = new ctor( x.length );
  			out = matrix( d, x.shape, dt );
  		} else {
  			out = x;
  		}
  		return cdf5( out, x, opts.alpha, opts.beta );
  	}
  	if ( isTypedArrayLike( x ) ) {
  		if ( opts.copy === false ) {
  			out = x;
  		} else {
  			dt = opts.dtype || 'float64';
  			ctor = ctors( dt );
  			if ( ctor === null ) {
  				throw new Error( 'cdf()::invalid option. Data type option does not have a corresponding array constructor. Option: `' + dt + '`.' );
  			}
  			out = new ctor( x.length );
  		}
  		return cdf6( out, x, opts.alpha, opts.beta );
  	}
  	if ( isArrayLike( x ) ) {
  		// Handle deepset first...
  		if ( opts.path ) {
  			opts.sep = opts.sep || '.';
  			return cdf4( x, opts.alpha, opts.beta, opts.path, opts.sep );
  		}
  		// Handle regular and accessor arrays next...
  		if ( opts.copy === false ) {
  			out = x;
  		}
  		else if ( opts.dtype ) {
  			ctor = ctors( opts.dtype );
  			if ( ctor === null ) {
  				throw new TypeError( 'cdf()::invalid option. Data type option does not have a corresponding array constructor. Option: `' + opts.dtype + '`.' );
  			}
  			out = new ctor( x.length );
  		}
  		else {
  			out = new Array( x.length );
  		}
  		if ( opts.accessor ) {
  			return cdf3( out, x, opts.alpha, opts.beta, opts.accessor );
  		}
  		return cdf2( out, x, opts.alpha, opts.beta );
  	}
  	return NaN;
  } // end FUNCTION cdf()
  
  
  // EXPORTS //
  
  module.exports = cdf;
  