<?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 LogNormal
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{
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use ArrayEnabled;
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/**
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* LOGNORMDIST.
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*
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* Returns the cumulative lognormal distribution of x, where ln(x) is normally distributed
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* with parameters mean and standard_dev.
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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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* @param mixed $mean Mean value as a float
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* Or can be an array of values
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* @param mixed $stdDev Standard Deviation as a float
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* Or can be an array of values
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*
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* @return array|float|string The result, or a string containing an error
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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 cumulative(mixed $value, mixed $mean, mixed $stdDev)
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{
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if (is_array($value) || is_array($mean) || is_array($stdDev)) {
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return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $mean, $stdDev);
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}
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try {
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$value = DistributionValidations::validateFloat($value);
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$mean = DistributionValidations::validateFloat($mean);
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$stdDev = DistributionValidations::validateFloat($stdDev);
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} catch (Exception $e) {
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return $e->getMessage();
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}
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if (($value <= 0) || ($stdDev <= 0)) {
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return ExcelError::NAN();
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}
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return StandardNormal::cumulative((log($value) - $mean) / $stdDev);
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}
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/**
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* LOGNORM.DIST.
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*
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* Returns the lognormal distribution of x, where ln(x) is normally distributed
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* with parameters mean and standard_dev.
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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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* @param mixed $mean Mean value as a float
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* Or can be an array of values
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* @param mixed $stdDev Standard Deviation as a float
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* Or can be an array of values
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* @param mixed $cumulative Boolean value indicating if we want the cdf (true) or the pdf (false)
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* Or can be an array of values
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*
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* @return array|float|string The result, or a string containing an error
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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(mixed $value, mixed $mean, mixed $stdDev, mixed $cumulative = false)
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{
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if (is_array($value) || is_array($mean) || is_array($stdDev) || is_array($cumulative)) {
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return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $mean, $stdDev, $cumulative);
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}
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try {
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$value = DistributionValidations::validateFloat($value);
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$mean = DistributionValidations::validateFloat($mean);
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$stdDev = DistributionValidations::validateFloat($stdDev);
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$cumulative = DistributionValidations::validateBool($cumulative);
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} catch (Exception $e) {
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return $e->getMessage();
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}
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if (($value <= 0) || ($stdDev <= 0)) {
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return ExcelError::NAN();
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}
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if ($cumulative === true) {
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return StandardNormal::distribution((log($value) - $mean) / $stdDev, true);
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}
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return (1 / (sqrt(2 * M_PI) * $stdDev * $value))
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* exp(0 - ((log($value) - $mean) ** 2 / (2 * $stdDev ** 2)));
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}
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/**
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* LOGINV.
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*
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* Returns the inverse of the lognormal cumulative distribution
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*
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* @param mixed $probability Float probability for which we want the value
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* Or can be an array of values
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* @param mixed $mean Mean Value as a float
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* Or can be an array of values
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* @param mixed $stdDev Standard Deviation as a float
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* Or can be an array of values
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*
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* @return array|float|string The result, or a string containing an error
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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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* @TODO Try implementing P J Acklam's refinement algorithm for greater
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* accuracy if I can get my head round the mathematics
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* (as described at) http://home.online.no/~pjacklam/notes/invnorm/
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*/
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public static function inverse(mixed $probability, mixed $mean, mixed $stdDev): array|string|float
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{
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if (is_array($probability) || is_array($mean) || is_array($stdDev)) {
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return self::evaluateArrayArguments([self::class, __FUNCTION__], $probability, $mean, $stdDev);
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}
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try {
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$probability = DistributionValidations::validateProbability($probability);
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$mean = DistributionValidations::validateFloat($mean);
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$stdDev = DistributionValidations::validateFloat($stdDev);
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} catch (Exception $e) {
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return $e->getMessage();
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}
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if ($stdDev <= 0) {
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return ExcelError::NAN();
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}
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/** @var float $inverse */
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$inverse = StandardNormal::inverse($probability);
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return exp($mean + $stdDev * $inverse);
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}
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}
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