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<?php
namespace PhpOffice\PhpSpreadsheet\Calculation\Statistical;
use PhpOffice\PhpSpreadsheet\Calculation\Functions;
class Deviations
{
/**
* DEVSQ.
*
* Returns the sum of squares of deviations of data points from their sample mean.
*
* Excel Function:
* DEVSQ(value1[,value2[, ...]])
*
* @param mixed ...$args Data values
*
* @return float|string
*/
public static function sumSquares(...$args)
{
$aArgs = Functions::flattenArrayIndexed($args);
$aMean = Averages::average($aArgs);
if (!is_numeric($aMean)) {
return Functions::NAN();
}
// Return value
$returnValue = 0.0;
$aCount = -1;
foreach ($aArgs as $k => $arg) {
// Is it a numeric value?
if (
(is_bool($arg)) &&
((!Functions::isCellValue($k)) ||
(Functions::getCompatibilityMode() == Functions::COMPATIBILITY_OPENOFFICE))
) {
$arg = (int) $arg;
}
if ((is_numeric($arg)) && (!is_string($arg))) {
$returnValue += ($arg - $aMean) ** 2;
++$aCount;
}
}
return $aCount === 0 ? Functions::VALUE() : $returnValue;
}
/**
* KURT.
*
* Returns the kurtosis of a data set. Kurtosis characterizes the relative peakedness
* or flatness of a distribution compared with the normal distribution. Positive
* kurtosis indicates a relatively peaked distribution. Negative kurtosis indicates a
* relatively flat distribution.
*
* @param array ...$args Data Series
*
* @return float|string
*/
public static function kurtosis(...$args)
{
$aArgs = Functions::flattenArrayIndexed($args);
$mean = Averages::average($aArgs);
if (!is_numeric($mean)) {
return Functions::DIV0();
}
$stdDev = StandardDeviations::STDEV($aArgs);
if ($stdDev > 0) {
$count = $summer = 0;
foreach ($aArgs as $k => $arg) {
if ((is_bool($arg)) && (!Functions::isMatrixValue($k))) {
} else {
// Is it a numeric value?
if ((is_numeric($arg)) && (!is_string($arg))) {
$summer += (($arg - $mean) / $stdDev) ** 4;
++$count;
}
}
}
if ($count > 3) {
return $summer * ($count * ($count + 1) /
(($count - 1) * ($count - 2) * ($count - 3))) - (3 * ($count - 1) ** 2 /
(($count - 2) * ($count - 3)));
}
}
return Functions::DIV0();
}
/**
* SKEW.
*
* Returns the skewness of a distribution. Skewness characterizes the degree of asymmetry
* of a distribution around its mean. Positive skewness indicates a distribution with an
* asymmetric tail extending toward more positive values. Negative skewness indicates a
* distribution with an asymmetric tail extending toward more negative values.
*
* @param array ...$args Data Series
*
* @return float|string The result, or a string containing an error
*/
public static function skew(...$args)
{
$aArgs = Functions::flattenArrayIndexed($args);
$mean = Averages::average($aArgs);
if (!is_numeric($mean)) {
return Functions::DIV0();
}
$stdDev = StandardDeviations::STDEV($aArgs);
if ($stdDev === 0.0 || is_string($stdDev)) {
return Functions::DIV0();
}
$count = $summer = 0;
// Loop through arguments
foreach ($aArgs as $k => $arg) {
if ((is_bool($arg)) && (!Functions::isMatrixValue($k))) {
} elseif (!is_numeric($arg)) {
return Functions::VALUE();
} else {
// Is it a numeric value?
if ((is_numeric($arg)) && (!is_string($arg))) {
$summer += (($arg - $mean) / $stdDev) ** 3;
++$count;
}
}
}
if ($count > 2) {
return $summer * ($count / (($count - 1) * ($count - 2)));
}
return Functions::DIV0();
}
}