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lib/PhpSpreadsheet/Calculation/Statistical/Distributions/NewtonRaphson.php

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+<?php
+
+namespace PhpOffice\PhpSpreadsheet\Calculation\Statistical\Distributions;
+
+use PhpOffice\PhpSpreadsheet\Calculation\Functions;
+use PhpOffice\PhpSpreadsheet\Calculation\Information\ExcelError;
+
+class NewtonRaphson
+{
+    private const MAX_ITERATIONS = 256;
+
+    /** @var callable */
+    protected $callback;
+
+    public function __construct(callable $callback)
+    {
+        $this->callback = $callback;
+    }
+
+    public function execute(float $probability): string|int|float
+    {
+        $xLo = 100;
+        $xHi = 0;
+
+        $dx = 1;
+        $x = $xNew = 1;
+        $i = 0;
+
+        while ((abs($dx) > Functions::PRECISION) && ($i++ < self::MAX_ITERATIONS)) {
+            // Apply Newton-Raphson step
+            $result = call_user_func($this->callback, $x);
+            $error = $result - $probability;
+
+            if ($error == 0.0) {
+                $dx = 0;
+            } elseif ($error < 0.0) {
+                $xLo = $x;
+            } else {
+                $xHi = $x;
+            }
+
+            // Avoid division by zero
+            if ($result != 0.0) {
+                $dx = $error / $result;
+                $xNew = $x - $dx;
+            }
+
+            // If the NR fails to converge (which for example may be the
+            // case if the initial guess is too rough) we apply a bisection
+            // step to determine a more narrow interval around the root.
+            if (($xNew < $xLo) || ($xNew > $xHi) || ($result == 0.0)) {
+                $xNew = ($xLo + $xHi) / 2;
+                $dx = $xNew - $x;
+            }
+            $x = $xNew;
+        }
+
+        if ($i == self::MAX_ITERATIONS) {
+            return ExcelError::NA();
+        }
+
+        return $x;
+    }
+}