lib/filter/outliers/mild.js
function filter( FLG ) {
		/**
		* FUNCTION: filter( data )
		*	Defines the data filter.
		*
		* @param {number} data - numeric stream data
		* @returns {number} filtered data
		*/
		return function filter( data ) {
			var qValues, iqr,
				bounds = new Array( 4 ),
				idx, d, outliers = [];

			// Convert a comma delimited string into an array:
			data = JSON.parse( '[' + data + ']' );

			// Sort the data:
			data = sort( data );

			// Compute the quartiles:
			qValues = quartiles( data );

			// Compute the inter-quartile range:
			iqr = qValues[ 1 ] - qValues[ 0 ];

			// Compute the outlier bounds:
			bounds[ 0 ] = qValues[ 0 ] - ( 3.0*iqr );
			bounds[ 1 ] = qValues[ 0 ] - ( 1.5*iqr );
			bounds[ 2 ] = qValues[ 1 ] + ( 1.5*iqr );
			bounds[ 3 ] = qValues[ 1 ] + ( 3.0*iqr );

			// Find the values less than the mild lower bound but greater than the extreme lower bound:
			idx = 0;
			d = data[ idx ][ 1 ];
			while ( d < bounds[ 1 ] ) {
				if ( d > bounds[ 0 ] ) {
					outliers.push( ( FLG ) ? data[idx] : d );
				}
				idx += 1;
				d = data[ idx][ 1 ];
			}

			// Find the values greater than the mild upper bound but less than the extreme upper bound:
			idx = data.length - 1;
			d = data[ idx ][ 1 ];
			while ( d > bounds[ 2 ] ) {
				if ( d < bounds[ 3 ] ) {
					outliers.push( ( FLG ) ? data[idx] : d );
				}
				idx = idx - 1;
				d = data[ idx ][ 1 ];
			}

			// Return the outliers:
			return outliers;
		}; // end FUNCTION filter()
	}
function filter( FLG ) {
		/**
		* FUNCTION: filter( data )
		*	Defines the data filter.
		*
		* @param {number} data - numeric stream data
		* @returns {number} filtered data
		*/
		return function filter( data ) {
			var qValues, iqr,
				bounds = new Array( 4 ),
				idx, d, outliers = [];

			// Convert a comma delimited string into an array:
			data = JSON.parse( '[' + data + ']' );

			// Sort the data:
			data = sort( data );

			// Compute the quartiles:
			qValues = quartiles( data );

			// Compute the inter-quartile range:
			iqr = qValues[ 1 ] - qValues[ 0 ];

			// Compute the outlier bounds:
			bounds[ 0 ] = qValues[ 0 ] - ( 3.0*iqr );
			bounds[ 1 ] = qValues[ 0 ] - ( 1.5*iqr );
			bounds[ 2 ] = qValues[ 1 ] + ( 1.5*iqr );
			bounds[ 3 ] = qValues[ 1 ] + ( 3.0*iqr );

			// Find the values less than the mild lower bound but greater than the extreme lower bound:
			idx = 0;
			d = data[ idx ][ 1 ];
			while ( d < bounds[ 1 ] ) {
				if ( d > bounds[ 0 ] ) {
					outliers.push( ( FLG ) ? data[idx] : d );
				}
				idx += 1;
				d = data[ idx][ 1 ];
			}

			// Find the values greater than the mild upper bound but less than the extreme upper bound:
			idx = data.length - 1;
			d = data[ idx ][ 1 ];
			while ( d > bounds[ 2 ] ) {
				if ( d < bounds[ 3 ] ) {
					outliers.push( ( FLG ) ? data[idx] : d );
				}
				idx = idx - 1;
				d = data[ idx ][ 1 ];
			}

			// Return the outliers:
			return outliers;
		}; // end FUNCTION filter()
	}
end FUNCTION quantile() 
FUNCTION: filter( FLG )
Returns a data filter function.

@private
@param {boolean} FLG - flag indicating whether to retain outlier index
@returns {function} data filter function