diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/bestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/bestFitClass.php
new file mode 100644
index 0000000..9ae8b00
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/bestFitClass.php
@@ -0,0 +1,432 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+/**
+ * PHPExcel_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Best_Fit
+{
+	/**
+	 * Indicator flag for a calculation error
+	 *
+	 * @var	boolean
+	 **/
+	protected $_error				= False;
+
+	/**
+	 * Algorithm type to use for best-fit
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType			= 'undetermined';
+
+	/**
+	 * Number of entries in the sets of x- and y-value arrays
+	 *
+	 * @var	int
+	 **/
+	protected $_valueCount			= 0;
+
+	/**
+	 * X-value dataseries of values
+	 *
+	 * @var	float[]
+	 **/
+	protected $_xValues				= array();
+
+	/**
+	 * Y-value dataseries of values
+	 *
+	 * @var	float[]
+	 **/
+	protected $_yValues				= array();
+
+	/**
+	 * Flag indicating whether values should be adjusted to Y=0
+	 *
+	 * @var	boolean
+	 **/
+	protected $_adjustToZero		= False;
+
+	/**
+	 * Y-value series of best-fit values
+	 *
+	 * @var	float[]
+	 **/
+	protected $_yBestFitValues		= array();
+
+	protected $_goodnessOfFit 		= 1;
+
+	protected $_stdevOfResiduals	= 0;
+
+	protected $_covariance			= 0;
+
+	protected $_correlation			= 0;
+
+	protected $_SSRegression		= 0;
+
+	protected $_SSResiduals			= 0;
+
+	protected $_DFResiduals			= 0;
+
+	protected $_F					= 0;
+
+	protected $_slope				= 0;
+
+	protected $_slopeSE				= 0;
+
+	protected $_intersect			= 0;
+
+	protected $_intersectSE			= 0;
+
+	protected $_Xoffset				= 0;
+
+	protected $_Yoffset				= 0;
+
+
+	public function getError() {
+		return $this->_error;
+	}	//	function getBestFitType()
+
+
+	public function getBestFitType() {
+		return $this->_bestFitType;
+	}	//	function getBestFitType()
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 */
+	public function getValueOfYForX($xValue) {
+		return False;
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 */
+	public function getValueOfXForY($yValue) {
+		return False;
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the original set of X-Values
+	 *
+	 * @return	 float[]				X-Values
+	 */
+	public function getXValues() {
+		return $this->_xValues;
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 */
+	public function getEquation($dp=0) {
+		return False;
+	}	//	function getEquation()
+
+
+	/**
+	 * Return the Slope of the line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 */
+	public function getSlope($dp=0) {
+		if ($dp != 0) {
+			return round($this->_slope,$dp);
+		}
+		return $this->_slope;
+	}	//	function getSlope()
+
+
+	/**
+	 * Return the standard error of the Slope
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 */
+	public function getSlopeSE($dp=0) {
+		if ($dp != 0) {
+			return round($this->_slopeSE,$dp);
+		}
+		return $this->_slopeSE;
+	}	//	function getSlopeSE()
+
+
+	/**
+	 * Return the Value of X where it intersects Y = 0
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 */
+	public function getIntersect($dp=0) {
+		if ($dp != 0) {
+			return round($this->_intersect,$dp);
+		}
+		return $this->_intersect;
+	}	//	function getIntersect()
+
+
+	/**
+	 * Return the standard error of the Intersect
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 */
+	public function getIntersectSE($dp=0) {
+		if ($dp != 0) {
+			return round($this->_intersectSE,$dp);
+		}
+		return $this->_intersectSE;
+	}	//	function getIntersectSE()
+
+
+	/**
+	 * Return the goodness of fit for this regression
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to return
+	 * @return	 float
+	 */
+	public function getGoodnessOfFit($dp=0) {
+		if ($dp != 0) {
+			return round($this->_goodnessOfFit,$dp);
+		}
+		return $this->_goodnessOfFit;
+	}	//	function getGoodnessOfFit()
+
+
+	public function getGoodnessOfFitPercent($dp=0) {
+		if ($dp != 0) {
+			return round($this->_goodnessOfFit * 100,$dp);
+		}
+		return $this->_goodnessOfFit * 100;
+	}	//	function getGoodnessOfFitPercent()
+
+
+	/**
+	 * Return the standard deviation of the residuals for this regression
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to return
+	 * @return	 float
+	 */
+	public function getStdevOfResiduals($dp=0) {
+		if ($dp != 0) {
+			return round($this->_stdevOfResiduals,$dp);
+		}
+		return $this->_stdevOfResiduals;
+	}	//	function getStdevOfResiduals()
+
+
+	public function getSSRegression($dp=0) {
+		if ($dp != 0) {
+			return round($this->_SSRegression,$dp);
+		}
+		return $this->_SSRegression;
+	}	//	function getSSRegression()
+
+
+	public function getSSResiduals($dp=0) {
+		if ($dp != 0) {
+			return round($this->_SSResiduals,$dp);
+		}
+		return $this->_SSResiduals;
+	}	//	function getSSResiduals()
+
+
+	public function getDFResiduals($dp=0) {
+		if ($dp != 0) {
+			return round($this->_DFResiduals,$dp);
+		}
+		return $this->_DFResiduals;
+	}	//	function getDFResiduals()
+
+
+	public function getF($dp=0) {
+		if ($dp != 0) {
+			return round($this->_F,$dp);
+		}
+		return $this->_F;
+	}	//	function getF()
+
+
+	public function getCovariance($dp=0) {
+		if ($dp != 0) {
+			return round($this->_covariance,$dp);
+		}
+		return $this->_covariance;
+	}	//	function getCovariance()
+
+
+	public function getCorrelation($dp=0) {
+		if ($dp != 0) {
+			return round($this->_correlation,$dp);
+		}
+		return $this->_correlation;
+	}	//	function getCorrelation()
+
+
+	public function getYBestFitValues() {
+		return $this->_yBestFitValues;
+	}	//	function getYBestFitValues()
+
+
+	protected function _calculateGoodnessOfFit($sumX,$sumY,$sumX2,$sumY2,$sumXY,$meanX,$meanY, $const) {
+		$SSres = $SScov = $SScor = $SStot = $SSsex = 0.0;
+		foreach($this->_xValues as $xKey => $xValue) {
+			$bestFitY = $this->_yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
+
+			$SSres += ($this->_yValues[$xKey] - $bestFitY) * ($this->_yValues[$xKey] - $bestFitY);
+			if ($const) {
+				$SStot += ($this->_yValues[$xKey] - $meanY) * ($this->_yValues[$xKey] - $meanY);
+			} else {
+				$SStot += $this->_yValues[$xKey] * $this->_yValues[$xKey];
+			}
+			$SScov += ($this->_xValues[$xKey] - $meanX) * ($this->_yValues[$xKey] - $meanY);
+			if ($const) {
+				$SSsex += ($this->_xValues[$xKey] - $meanX) * ($this->_xValues[$xKey] - $meanX);
+			} else {
+				$SSsex += $this->_xValues[$xKey] * $this->_xValues[$xKey];
+			}
+		}
+
+		$this->_SSResiduals = $SSres;
+		$this->_DFResiduals = $this->_valueCount - 1 - $const;
+
+		if ($this->_DFResiduals == 0.0) {
+			$this->_stdevOfResiduals = 0.0;
+		} else {
+			$this->_stdevOfResiduals = sqrt($SSres / $this->_DFResiduals);
+		}
+		if (($SStot == 0.0) || ($SSres == $SStot)) {
+			$this->_goodnessOfFit = 1;
+		} else {
+			$this->_goodnessOfFit = 1 - ($SSres / $SStot);
+		}
+
+		$this->_SSRegression = $this->_goodnessOfFit * $SStot;
+		$this->_covariance = $SScov / $this->_valueCount;
+		$this->_correlation = ($this->_valueCount * $sumXY - $sumX * $sumY) / sqrt(($this->_valueCount * $sumX2 - pow($sumX,2)) * ($this->_valueCount * $sumY2 - pow($sumY,2)));
+		$this->_slopeSE = $this->_stdevOfResiduals / sqrt($SSsex);
+		$this->_intersectSE = $this->_stdevOfResiduals * sqrt(1 / ($this->_valueCount - ($sumX * $sumX) / $sumX2));
+		if ($this->_SSResiduals != 0.0) {
+			if ($this->_DFResiduals == 0.0) {
+				$this->_F = 0.0;
+			} else {
+				$this->_F = $this->_SSRegression / ($this->_SSResiduals / $this->_DFResiduals);
+			}
+		} else {
+			if ($this->_DFResiduals == 0.0) {
+				$this->_F = 0.0;
+			} else {
+				$this->_F = $this->_SSRegression / $this->_DFResiduals;
+			}
+		}
+	}	//	function _calculateGoodnessOfFit()
+
+
+	protected function _leastSquareFit($yValues, $xValues, $const) {
+		// calculate sums
+		$x_sum = array_sum($xValues);
+		$y_sum = array_sum($yValues);
+		$meanX = $x_sum / $this->_valueCount;
+		$meanY = $y_sum / $this->_valueCount;
+		$mBase = $mDivisor = $xx_sum = $xy_sum = $yy_sum = 0.0;
+		for($i = 0; $i < $this->_valueCount; ++$i) {
+			$xy_sum += $xValues[$i] * $yValues[$i];
+			$xx_sum += $xValues[$i] * $xValues[$i];
+			$yy_sum += $yValues[$i] * $yValues[$i];
+
+			if ($const) {
+				$mBase += ($xValues[$i] - $meanX) * ($yValues[$i] - $meanY);
+				$mDivisor += ($xValues[$i] - $meanX) * ($xValues[$i] - $meanX);
+			} else {
+				$mBase += $xValues[$i] * $yValues[$i];
+				$mDivisor += $xValues[$i] * $xValues[$i];
+			}
+		}
+
+		// calculate slope
+//		$this->_slope = (($this->_valueCount * $xy_sum) - ($x_sum * $y_sum)) / (($this->_valueCount * $xx_sum) - ($x_sum * $x_sum));
+		$this->_slope = $mBase / $mDivisor;
+
+		// calculate intersect
+//		$this->_intersect = ($y_sum - ($this->_slope * $x_sum)) / $this->_valueCount;
+		if ($const) {
+			$this->_intersect = $meanY - ($this->_slope * $meanX);
+		} else {
+			$this->_intersect = 0;
+		}
+
+		$this->_calculateGoodnessOfFit($x_sum,$y_sum,$xx_sum,$yy_sum,$xy_sum,$meanX,$meanY,$const);
+	}	//	function _leastSquareFit()
+
+
+	/**
+	 * Define the regression
+	 *
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	function __construct($yValues, $xValues=array(), $const=True) {
+		//	Calculate number of points
+		$nY = count($yValues);
+		$nX = count($xValues);
+
+		//	Define X Values if necessary
+		if ($nX == 0) {
+			$xValues = range(1,$nY);
+			$nX = $nY;
+		} elseif ($nY != $nX) {
+			//	Ensure both arrays of points are the same size
+			$this->_error = True;
+			return False;
+		}
+
+		$this->_valueCount = $nY;
+		$this->_xValues = $xValues;
+		$this->_yValues = $yValues;
+	}	//	function __construct()
+
+}	//	class bestFit
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/exponentialBestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/exponentialBestFitClass.php
new file mode 100644
index 0000000..b524b5f
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/exponentialBestFitClass.php
@@ -0,0 +1,148 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
+
+
+/**
+ * PHPExcel_Exponential_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Exponential_Best_Fit extends PHPExcel_Best_Fit
+{
+	/**
+	 * Algorithm type to use for best-fit
+	 * (Name of this trend class)
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType		= 'exponential';
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 **/
+	public function getValueOfYForX($xValue) {
+		return $this->getIntersect() * pow($this->getSlope(),($xValue - $this->_Xoffset));
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 **/
+	public function getValueOfXForY($yValue) {
+		return log(($yValue + $this->_Yoffset) / $this->getIntersect()) / log($this->getSlope());
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getEquation($dp=0) {
+		$slope = $this->getSlope($dp);
+		$intersect = $this->getIntersect($dp);
+
+		return 'Y = '.$intersect.' * '.$slope.'^X';
+	}	//	function getEquation()
+
+
+	/**
+	 * Return the Slope of the line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getSlope($dp=0) {
+		if ($dp != 0) {
+			return round(exp($this->_slope),$dp);
+		}
+		return exp($this->_slope);
+	}	//	function getSlope()
+
+
+	/**
+	 * Return the Value of X where it intersects Y = 0
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getIntersect($dp=0) {
+		if ($dp != 0) {
+			return round(exp($this->_intersect),$dp);
+		}
+		return exp($this->_intersect);
+	}	//	function getIntersect()
+
+
+	/**
+	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	 float[]	$yValues	The set of Y-values for this regression
+	 * @param	 float[]	$xValues	The set of X-values for this regression
+	 * @param	 boolean	$const
+	 */
+	private function _exponential_regression($yValues, $xValues, $const) {
+		foreach($yValues as &$value) {
+			if ($value < 0.0) {
+				$value = 0 - log(abs($value));
+			} elseif ($value > 0.0) {
+				$value = log($value);
+			}
+		}
+		unset($value);
+
+		$this->_leastSquareFit($yValues, $xValues, $const);
+	}	//	function _exponential_regression()
+
+
+	/**
+	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	function __construct($yValues, $xValues=array(), $const=True) {
+		if (parent::__construct($yValues, $xValues) !== False) {
+			$this->_exponential_regression($yValues, $xValues, $const);
+		}
+	}	//	function __construct()
+
+}	//	class exponentialBestFit
\ No newline at end of file
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/linearBestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/linearBestFitClass.php
new file mode 100644
index 0000000..7d811aa
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/linearBestFitClass.php
@@ -0,0 +1,111 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
+
+
+/**
+ * PHPExcel_Linear_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Linear_Best_Fit extends PHPExcel_Best_Fit
+{
+	/**
+	 * Algorithm type to use for best-fit
+	 * (Name of this trend class)
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType		= 'linear';
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 **/
+	public function getValueOfYForX($xValue) {
+		return $this->getIntersect() + $this->getSlope() * $xValue;
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 **/
+	public function getValueOfXForY($yValue) {
+		return ($yValue - $this->getIntersect()) / $this->getSlope();
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getEquation($dp=0) {
+		$slope = $this->getSlope($dp);
+		$intersect = $this->getIntersect($dp);
+
+		return 'Y = '.$intersect.' + '.$slope.' * X';
+	}	//	function getEquation()
+
+
+	/**
+	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	 float[]	$yValues	The set of Y-values for this regression
+	 * @param	 float[]	$xValues	The set of X-values for this regression
+	 * @param	 boolean	$const
+	 */
+	private function _linear_regression($yValues, $xValues, $const) {
+		$this->_leastSquareFit($yValues, $xValues,$const);
+	}	//	function _linear_regression()
+
+
+	/**
+	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	function __construct($yValues, $xValues=array(), $const=True) {
+		if (parent::__construct($yValues, $xValues) !== False) {
+			$this->_linear_regression($yValues, $xValues, $const);
+		}
+	}	//	function __construct()
+
+}	//	class linearBestFit
\ No newline at end of file
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/logarithmicBestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/logarithmicBestFitClass.php
new file mode 100644
index 0000000..b43cd5e
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/logarithmicBestFitClass.php
@@ -0,0 +1,120 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once(PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php');
+
+
+/**
+ * PHPExcel_Logarithmic_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Logarithmic_Best_Fit extends PHPExcel_Best_Fit
+{
+	/**
+	 * Algorithm type to use for best-fit
+	 * (Name of this trend class)
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType		= 'logarithmic';
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 **/
+	public function getValueOfYForX($xValue) {
+		return $this->getIntersect() + $this->getSlope() * log($xValue - $this->_Xoffset);
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 **/
+	public function getValueOfXForY($yValue) {
+		return exp(($yValue - $this->getIntersect()) / $this->getSlope());
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getEquation($dp=0) {
+		$slope = $this->getSlope($dp);
+		$intersect = $this->getIntersect($dp);
+
+		return 'Y = '.$intersect.' + '.$slope.' * log(X)';
+	}	//	function getEquation()
+
+
+	/**
+	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	 float[]	$yValues	The set of Y-values for this regression
+	 * @param	 float[]	$xValues	The set of X-values for this regression
+	 * @param	 boolean	$const
+	 */
+	private function _logarithmic_regression($yValues, $xValues, $const) {
+		foreach($xValues as &$value) {
+			if ($value < 0.0) {
+				$value = 0 - log(abs($value));
+			} elseif ($value > 0.0) {
+				$value = log($value);
+			}
+		}
+		unset($value);
+
+		$this->_leastSquareFit($yValues, $xValues, $const);
+	}	//	function _logarithmic_regression()
+
+
+	/**
+	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	function __construct($yValues, $xValues=array(), $const=True) {
+		if (parent::__construct($yValues, $xValues) !== False) {
+			$this->_logarithmic_regression($yValues, $xValues, $const);
+		}
+	}	//	function __construct()
+
+}	//	class logarithmicBestFit
\ No newline at end of file
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/polynomialBestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/polynomialBestFitClass.php
new file mode 100644
index 0000000..3d329eb
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/polynomialBestFitClass.php
@@ -0,0 +1,224 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php';
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/JAMA/Matrix.php';
+
+
+/**
+ * PHPExcel_Polynomial_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Polynomial_Best_Fit extends PHPExcel_Best_Fit
+{
+	/**
+	 * Algorithm type to use for best-fit
+	 * (Name of this trend class)
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType		= 'polynomial';
+
+	/**
+	 * Polynomial order
+	 *
+	 * @protected
+	 * @var	int
+	 **/
+	protected $_order			= 0;
+
+
+	/**
+	 * Return the order of this polynomial
+	 *
+	 * @return	 int
+	 **/
+	public function getOrder() {
+		return $this->_order;
+	}	//	function getOrder()
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 **/
+	public function getValueOfYForX($xValue) {
+		$retVal = $this->getIntersect();
+		$slope = $this->getSlope();
+		foreach($slope as $key => $value) {
+			if ($value != 0.0) {
+				$retVal += $value * pow($xValue, $key + 1);
+			}
+		}
+		return $retVal;
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 **/
+	public function getValueOfXForY($yValue) {
+		return ($yValue - $this->getIntersect()) / $this->getSlope();
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getEquation($dp=0) {
+		$slope = $this->getSlope($dp);
+		$intersect = $this->getIntersect($dp);
+
+		$equation = 'Y = '.$intersect;
+		foreach($slope as $key => $value) {
+			if ($value != 0.0) {
+				$equation .= ' + '.$value.' * X';
+				if ($key > 0) {
+					$equation .= '^'.($key + 1);
+				}
+			}
+		}
+		return $equation;
+	}	//	function getEquation()
+
+
+	/**
+	 * Return the Slope of the line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getSlope($dp=0) {
+		if ($dp != 0) {
+			$coefficients = array();
+			foreach($this->_slope as $coefficient) {
+				$coefficients[] = round($coefficient,$dp);
+			}
+			return $coefficients;
+		}
+		return $this->_slope;
+	}	//	function getSlope()
+
+
+	public function getCoefficients($dp=0) {
+		return array_merge(array($this->getIntersect($dp)),$this->getSlope($dp));
+	}	//	function getCoefficients()
+
+
+	/**
+	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	int			$order		Order of Polynomial for this regression
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	private function _polynomial_regression($order, $yValues, $xValues, $const) {
+		// calculate sums
+		$x_sum = array_sum($xValues);
+		$y_sum = array_sum($yValues);
+		$xx_sum = $xy_sum = 0;
+		for($i = 0; $i < $this->_valueCount; ++$i) {
+			$xy_sum += $xValues[$i] * $yValues[$i];
+			$xx_sum += $xValues[$i] * $xValues[$i];
+			$yy_sum += $yValues[$i] * $yValues[$i];
+		}
+		/*
+		 *	This routine uses logic from the PHP port of polyfit version 0.1
+		 *	written by Michael Bommarito and Paul Meagher
+		 *
+		 *	The function fits a polynomial function of order $order through
+		 *	a series of x-y data points using least squares.
+		 *
+		 */
+		for ($i = 0; $i < $this->_valueCount; ++$i) {
+			for ($j = 0; $j <= $order; ++$j) {
+				$A[$i][$j] = pow($xValues[$i], $j);
+			}
+		}
+		for ($i=0; $i < $this->_valueCount; ++$i) {
+			$B[$i] = array($yValues[$i]);
+		}
+		$matrixA = new Matrix($A);
+		$matrixB = new Matrix($B);
+		$C = $matrixA->solve($matrixB);
+
+		$coefficients = array();
+		for($i = 0; $i < $C->m; ++$i) {
+			$r = $C->get($i, 0);
+			if (abs($r) <= pow(10, -9)) {
+				$r = 0;
+			}
+			$coefficients[] = $r;
+		}
+
+		$this->_intersect = array_shift($coefficients);
+		$this->_slope = $coefficients;
+
+		$this->_calculateGoodnessOfFit($x_sum,$y_sum,$xx_sum,$yy_sum,$xy_sum);
+		foreach($this->_xValues as $xKey => $xValue) {
+			$this->_yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
+		}
+	}	//	function _polynomial_regression()
+
+
+	/**
+	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	int			$order		Order of Polynomial for this regression
+	 * @param	float[]		$yValues	The set of Y-values for this regression
+	 * @param	float[]		$xValues	The set of X-values for this regression
+	 * @param	boolean		$const
+	 */
+	function __construct($order, $yValues, $xValues=array(), $const=True) {
+		if (parent::__construct($yValues, $xValues) !== False) {
+			if ($order < $this->_valueCount) {
+				$this->_bestFitType .= '_'.$order;
+				$this->_order = $order;
+				$this->_polynomial_regression($order, $yValues, $xValues, $const);
+				if (($this->getGoodnessOfFit() < 0.0) || ($this->getGoodnessOfFit() > 1.0)) {
+					$this->_error = True;
+				}
+			} else {
+				$this->_error = True;
+			}
+		}
+	}	//	function __construct()
+
+}	//	class polynomialBestFit
\ No newline at end of file
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/powerBestFitClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/powerBestFitClass.php
new file mode 100644
index 0000000..832669c
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/powerBestFitClass.php
@@ -0,0 +1,142 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/bestFitClass.php';
+
+
+/**
+ * PHPExcel_Power_Best_Fit
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class PHPExcel_Power_Best_Fit extends PHPExcel_Best_Fit
+{
+	/**
+	 * Algorithm type to use for best-fit
+	 * (Name of this trend class)
+	 *
+	 * @var	string
+	 **/
+	protected $_bestFitType		= 'power';
+
+
+	/**
+	 * Return the Y-Value for a specified value of X
+	 *
+	 * @param	 float		$xValue			X-Value
+	 * @return	 float						Y-Value
+	 **/
+	public function getValueOfYForX($xValue) {
+		return $this->getIntersect() * pow(($xValue - $this->_Xoffset),$this->getSlope());
+	}	//	function getValueOfYForX()
+
+
+	/**
+	 * Return the X-Value for a specified value of Y
+	 *
+	 * @param	 float		$yValue			Y-Value
+	 * @return	 float						X-Value
+	 **/
+	public function getValueOfXForY($yValue) {
+		return pow((($yValue + $this->_Yoffset) / $this->getIntersect()),(1 / $this->getSlope()));
+	}	//	function getValueOfXForY()
+
+
+	/**
+	 * Return the Equation of the best-fit line
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getEquation($dp=0) {
+		$slope = $this->getSlope($dp);
+		$intersect = $this->getIntersect($dp);
+
+		return 'Y = '.$intersect.' * X^'.$slope;
+	}	//	function getEquation()
+
+
+	/**
+	 * Return the Value of X where it intersects Y = 0
+	 *
+	 * @param	 int		$dp		Number of places of decimal precision to display
+	 * @return	 string
+	 **/
+	public function getIntersect($dp=0) {
+		if ($dp != 0) {
+			return round(exp($this->_intersect),$dp);
+		}
+		return exp($this->_intersect);
+	}	//	function getIntersect()
+
+
+	/**
+	 * Execute the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	 float[]	$yValues	The set of Y-values for this regression
+	 * @param	 float[]	$xValues	The set of X-values for this regression
+	 * @param	 boolean	$const
+	 */
+	private function _power_regression($yValues, $xValues, $const) {
+		foreach($xValues as &$value) {
+			if ($value < 0.0) {
+				$value = 0 - log(abs($value));
+			} elseif ($value > 0.0) {
+				$value = log($value);
+			}
+		}
+		unset($value);
+		foreach($yValues as &$value) {
+			if ($value < 0.0) {
+				$value = 0 - log(abs($value));
+			} elseif ($value > 0.0) {
+				$value = log($value);
+			}
+		}
+		unset($value);
+
+		$this->_leastSquareFit($yValues, $xValues, $const);
+	}	//	function _power_regression()
+
+
+	/**
+	 * Define the regression and calculate the goodness of fit for a set of X and Y data values
+	 *
+	 * @param	 float[]	$yValues	The set of Y-values for this regression
+	 * @param	 float[]	$xValues	The set of X-values for this regression
+	 * @param	 boolean	$const
+	 */
+	function __construct($yValues, $xValues=array(), $const=True) {
+		if (parent::__construct($yValues, $xValues) !== False) {
+			$this->_power_regression($yValues, $xValues, $const);
+		}
+	}	//	function __construct()
+
+}	//	class powerBestFit
\ No newline at end of file
diff --git a/includes/PHPExcel/Classes/PHPExcel/Shared/trend/trendClass.php b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/trendClass.php
new file mode 100644
index 0000000..25d7eb1
--- /dev/null
+++ b/includes/PHPExcel/Classes/PHPExcel/Shared/trend/trendClass.php
@@ -0,0 +1,156 @@
+<?php
+/**
+ * PHPExcel
+ *
+ * Copyright (c) 2006 - 2014 PHPExcel
+ *
+ * This library is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * This library is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with this library; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt	LGPL
+ * @version    ##VERSION##, ##DATE##
+ */
+
+
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/linearBestFitClass.php';
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/logarithmicBestFitClass.php';
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/exponentialBestFitClass.php';
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/powerBestFitClass.php';
+require_once PHPEXCEL_ROOT . 'PHPExcel/Shared/trend/polynomialBestFitClass.php';
+
+
+/**
+ * PHPExcel_trendClass
+ *
+ * @category   PHPExcel
+ * @package    PHPExcel_Shared_Trend
+ * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
+ */
+class trendClass
+{
+	const TREND_LINEAR				= 'Linear';
+	const TREND_LOGARITHMIC			= 'Logarithmic';
+	const TREND_EXPONENTIAL			= 'Exponential';
+	const TREND_POWER				= 'Power';
+	const TREND_POLYNOMIAL_2		= 'Polynomial_2';
+	const TREND_POLYNOMIAL_3		= 'Polynomial_3';
+	const TREND_POLYNOMIAL_4		= 'Polynomial_4';
+	const TREND_POLYNOMIAL_5		= 'Polynomial_5';
+	const TREND_POLYNOMIAL_6		= 'Polynomial_6';
+	const TREND_BEST_FIT			= 'Bestfit';
+	const TREND_BEST_FIT_NO_POLY	= 'Bestfit_no_Polynomials';
+
+	/**
+	 * Names of the best-fit trend analysis methods
+	 *
+	 * @var string[]
+	 **/
+	private static $_trendTypes = array( self::TREND_LINEAR,
+										 self::TREND_LOGARITHMIC,
+										 self::TREND_EXPONENTIAL,
+										 self::TREND_POWER
+									   );
+	/**
+	 * Names of the best-fit trend polynomial orders
+	 *
+	 * @var string[]
+	 **/
+	private static $_trendTypePolyOrders = array( self::TREND_POLYNOMIAL_2,
+												  self::TREND_POLYNOMIAL_3,
+												  self::TREND_POLYNOMIAL_4,
+												  self::TREND_POLYNOMIAL_5,
+												  self::TREND_POLYNOMIAL_6
+											    );
+
+	/**
+	 * Cached results for each method when trying to identify which provides the best fit
+	 *
+	 * @var PHPExcel_Best_Fit[]
+	 **/
+	private static $_trendCache = array();
+
+
+	public static function calculate($trendType=self::TREND_BEST_FIT, $yValues, $xValues=array(), $const=True) {
+		//	Calculate number of points in each dataset
+		$nY = count($yValues);
+		$nX = count($xValues);
+
+		//	Define X Values if necessary
+		if ($nX == 0) {
+			$xValues = range(1,$nY);
+			$nX = $nY;
+		} elseif ($nY != $nX) {
+			//	Ensure both arrays of points are the same size
+			trigger_error("trend(): Number of elements in coordinate arrays do not match.", E_USER_ERROR);
+		}
+
+		$key = md5($trendType.$const.serialize($yValues).serialize($xValues));
+		//	Determine which trend method has been requested
+		switch ($trendType) {
+			//	Instantiate and return the class for the requested trend method
+			case self::TREND_LINEAR :
+			case self::TREND_LOGARITHMIC :
+			case self::TREND_EXPONENTIAL :
+			case self::TREND_POWER :
+				if (!isset(self::$_trendCache[$key])) {
+					$className = 'PHPExcel_'.$trendType.'_Best_Fit';
+					self::$_trendCache[$key] = new $className($yValues,$xValues,$const);
+				}
+				return self::$_trendCache[$key];
+				break;
+			case self::TREND_POLYNOMIAL_2	:
+			case self::TREND_POLYNOMIAL_3	:
+			case self::TREND_POLYNOMIAL_4	:
+			case self::TREND_POLYNOMIAL_5	:
+			case self::TREND_POLYNOMIAL_6	:
+				if (!isset(self::$_trendCache[$key])) {
+					$order = substr($trendType,-1);
+					self::$_trendCache[$key] = new PHPExcel_Polynomial_Best_Fit($order,$yValues,$xValues,$const);
+				}
+				return self::$_trendCache[$key];
+				break;
+			case self::TREND_BEST_FIT			:
+			case self::TREND_BEST_FIT_NO_POLY	:
+				//	If the request is to determine the best fit regression, then we test each trend line in turn
+				//	Start by generating an instance of each available trend method
+				foreach(self::$_trendTypes as $trendMethod) {
+					$className = 'PHPExcel_'.$trendMethod.'BestFit';
+					$bestFit[$trendMethod] = new $className($yValues,$xValues,$const);
+					$bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
+				}
+				if ($trendType != self::TREND_BEST_FIT_NO_POLY) {
+					foreach(self::$_trendTypePolyOrders as $trendMethod) {
+						$order = substr($trendMethod,-1);
+						$bestFit[$trendMethod] = new PHPExcel_Polynomial_Best_Fit($order,$yValues,$xValues,$const);
+						if ($bestFit[$trendMethod]->getError()) {
+							unset($bestFit[$trendMethod]);
+						} else {
+							$bestFitValue[$trendMethod] = $bestFit[$trendMethod]->getGoodnessOfFit();
+						}
+					}
+				}
+				//	Determine which of our trend lines is the best fit, and then we return the instance of that trend class
+				arsort($bestFitValue);
+				$bestFitType = key($bestFitValue);
+				return $bestFit[$bestFitType];
+				break;
+			default	:
+				return false;
+		}
+	}	//	function calculate()
+
+}	//	class trendClass
\ No newline at end of file