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75 lines
2.4 KiB
PHP
75 lines
2.4 KiB
PHP
<?php
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namespace PhpOffice\PhpSpreadsheet\Calculation\Statistical\Distributions;
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use PhpOffice\PhpSpreadsheet\Calculation\ArrayEnabled;
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use PhpOffice\PhpSpreadsheet\Calculation\Exception;
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use PhpOffice\PhpSpreadsheet\Calculation\Information\ExcelError;
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class Fisher
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{
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use ArrayEnabled;
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/**
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* FISHER.
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*
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* Returns the Fisher transformation at x. This transformation produces a function that
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* is normally distributed rather than skewed. Use this function to perform hypothesis
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* testing on the correlation coefficient.
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*
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* @param mixed $value Float value for which we want the probability
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* Or can be an array of values
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*
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* @return array|float|string
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* If an array of numbers is passed as an argument, then the returned result will also be an array
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* with the same dimensions
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*/
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public static function distribution($value)
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{
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if (\is_array($value)) {
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return self::evaluateSingleArgumentArray([self::class, __FUNCTION__], $value);
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}
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try {
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DistributionValidations::validateFloat($value);
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} catch (Exception $e) {
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return $e->getMessage();
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}
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if (($value <= -1) || ($value >= 1)) {
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return ExcelError::NAN();
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}
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return 0.5 * \log((1 + $value) / (1 - $value));
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}
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/**
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* FISHERINV.
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*
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* Returns the inverse of the Fisher transformation. Use this transformation when
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* analyzing correlations between ranges or arrays of data. If y = FISHER(x), then
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* FISHERINV(y) = x.
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*
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* @param mixed $probability Float probability at which you want to evaluate the distribution
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* Or can be an array of values
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*
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* @return array|float|string
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* If an array of numbers is passed as an argument, then the returned result will also be an array
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* with the same dimensions
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*/
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public static function inverse($probability)
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{
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if (\is_array($probability)) {
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return self::evaluateSingleArgumentArray([self::class, __FUNCTION__], $probability);
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}
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try {
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DistributionValidations::validateFloat($probability);
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} catch (Exception $e) {
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return $e->getMessage();
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}
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return (\exp(2 * $probability) - 1) / (\exp(2 * $probability) + 1);
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}
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}
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