tablepress / libraries / vendor / PhpSpreadsheet / Calculation / Statistical / Distributions / F.php

F.php in TablePress – Tables in WordPress made easy 3.4, at libraries/vendor/PhpSpreadsheet/Calculation/Statistical/Distributions/F.php

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1	<?php
2
3	namespace TablePress\PhpOffice\PhpSpreadsheet\Calculation\Statistical\Distributions;
4
5	use TablePress\PhpOffice\PhpSpreadsheet\Calculation\ArrayEnabled;
6	use TablePress\PhpOffice\PhpSpreadsheet\Calculation\Exception;
7	use TablePress\PhpOffice\PhpSpreadsheet\Calculation\Information\ExcelError;
8
9	class F
10	{
11	use ArrayEnabled;
12
13	/**
14	* F.DIST.
15	*
16	* Returns the F probability distribution.
17	* You can use this function to determine whether two data sets have different degrees of diversity.
18	* For example, you can examine the test scores of men and women entering high school, and determine
19	* if the variability in the females is different from that found in the males.
20	*
21	* @param mixed $value Float value for which we want the probability
22	* Or can be an array of values
23	* @param mixed $u The numerator degrees of freedom as an integer
24	* Or can be an array of values
25	* @param mixed $v The denominator degrees of freedom as an integer
26	* Or can be an array of values
27	* @param mixed $cumulative Boolean value indicating if we want the cdf (true) or the pdf (false)
28	* Or can be an array of values
29	*
30	* @return array<mixed>\|float\|string If an array of numbers is passed as an argument, then the returned result will also be an array
31	* with the same dimensions
32	*/
33	public static function distribution($value, $u, $v, $cumulative)
34	{
35	if (is_array($value) \|\| is_array($u) \|\| is_array($v) \|\| is_array($cumulative)) {
36	return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $u, $v, $cumulative);
37	}
38
39	try {
40	$value = DistributionValidations::validateFloat($value);
41	$u = DistributionValidations::validateInt($u);
42	$v = DistributionValidations::validateInt($v);
43	$cumulative = DistributionValidations::validateBool($cumulative);
44	} catch (Exception $e) {
45	return $e->getMessage();
46	}
47
48	if ($value < 0 \|\| $u < 1 \|\| $v < 1) {
49	return ExcelError::NAN();
50	}
51
52	if ($cumulative) {
53	$adjustedValue = ($u * $value) / ($u * $value + $v);
54
55	return Beta::incompleteBeta($adjustedValue, $u / 2, $v / 2);
56	}
57
58	if ($value == 0.0) {
59	if ($u === 2) {
60	return 1.0;
61	}
62
63	return ($u === 1) ? INF : 0.0;
64	}
65
66	// Log domain, so large degrees of freedom cannot overflow the Gamma ratio.
67	return exp(
68	Gamma::logGamma(($v + $u) / 2) - Gamma::logGamma($u / 2) - Gamma::logGamma($v / 2)
69	+ ($u / 2) * log($u / $v)
70	+ (($u - 2) / 2) * log($value)
71	- (($u + $v) / 2) * log(1 + ($u / $v) * $value)
72	);
73	}
74	}
75