diff --git a/src/PhpSpreadsheet/Shared/trend/bestFit.php b/src/PhpSpreadsheet/Shared/trend/bestFit.php
deleted file mode 100644
index afff9a8d..00000000
--- a/src/PhpSpreadsheet/Shared/trend/bestFit.php
+++ /dev/null
@@ -1,427 +0,0 @@
-<?php
-
-namespace PHPExcel\Shared\trend;
-
-/**
- * bestFit
- *
- * Copyright (c) 2006 - 2015 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 - 2015 PHPExcel (http://www.codeplex.com/PHPExcel)
- * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt    LGPL
- * @version    ##VERSION##, ##DATE##
- */
-class bestFit
-{
-    /**
-     * 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;
-    }
-
-
-    public function getBestFitType()
-    {
-        return $this->bestFitType;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * Return the original set of X-Values
-     *
-     * @return     float[]                X-Values
-     */
-    public function getXValues()
-    {
-        return $this->xValues;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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;
-    }
-
-    /**
-     * 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 $this->goodnessOfFit;
-    }
-
-    public function getGoodnessOfFitPercent($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->goodnessOfFit * 100, $dp);
-        }
-        return $this->goodnessOfFit * 100;
-    }
-
-    /**
-     * 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 $this->stdevOfResiduals;
-    }
-
-    public function getSSRegression($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->SSRegression, $dp);
-        }
-        return $this->SSRegression;
-    }
-
-    public function getSSResiduals($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->SSResiduals, $dp);
-        }
-        return $this->SSResiduals;
-    }
-
-    public function getDFResiduals($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->DFResiduals, $dp);
-        }
-        return $this->DFResiduals;
-    }
-
-    public function getF($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->f, $dp);
-        }
-        return $this->f;
-    }
-
-    public function getCovariance($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->covariance, $dp);
-        }
-        return $this->covariance;
-    }
-
-    public function getCorrelation($dp = 0)
-    {
-        if ($dp != 0) {
-            return round($this->correlation, $dp);
-        }
-        return $this->correlation;
-    }
-
-    public function getYBestFitValues()
-    {
-        return $this->yBestFitValues;
-    }
-
-    protected function calculateGoodnessOfFit($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 / $this->DFResiduals;
-            }
-        }
-    }
-
-    protected function leastSquareFit($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);
-    }
-
-    /**
-     * 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        $const
-     */
-    public function __construct($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;
-    }
-}