/**
* Pearson's Chi-Squared Goodness of Fit Test
*
* Tests whether a set of observations is significantly different than a
* set of expected values. To test goodness of fit against a distribution,
* use the appropriate distribution class to generate a corresponding set
* of expected values before calling this.
*
* @param array $observations The set of observations to be tested
* @param array $expected The set of expected values to be tested
* @param int $df The degrees of freedom in the test
* @return float The probability of getting the chi-squared statistic or more, the p-value
*/
public function chiSquareTest(array $observations, array $expected, $df)
{
$sum = 0;
$pairsTested = min(count($observations), count($observations));
for ($i = 0; $i < $pairsTested; $i++) {
if ($expected[$i] == 0) {
continue;
}
$sum += pow($observations[$i] - $expected[$i], 2) / $expected[$i];
}
return $this->chi->getSf($sum, $df);
}
/**
* Returns the moments of the distribution
*
* @param string $moments Which moments to compute. m for mean, v for variance, s for skew, k for kurtosis. Default 'mv'
* @return type array A dictionary containing the first four moments of the distribution
*/
public function stats($moments = 'mv')
{
return $this->calculator->getStats($moments, $this->k);
}
/**
* Returns a random float between $d1 and $d1 plus $d2
*
* @param float $d1 Degrees of freedom 1. Default 1.0
* @param float $d2 Degrees of freedom 2. Default 1.0
* @return float The random variate.
*/
public function getRvs($d1 = 1, $d2 = 1)
{
$x = $this->chi->getRvs($d1);
$y = $this->chi->getRvs($d2);
return $x / $d1 / ($y / $d2);
}
