PHPOffice /
PhpSpreadsheet
| @@ 1089-1135 (lines=47) @@ | ||
| 1086 | * |
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| 1087 | * @return float |
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| 1088 | */ |
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| 1089 | public static function CHIINV($probability, $degrees) |
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| 1090 | { |
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| 1091 | $probability = Functions::flattenSingleValue($probability); |
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| 1092 | $degrees = floor(Functions::flattenSingleValue($degrees)); |
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| 1093 | ||
| 1094 | if ((is_numeric($probability)) && (is_numeric($degrees))) { |
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| 1095 | $xLo = 100; |
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| 1096 | $xHi = 0; |
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| 1097 | ||
| 1098 | $x = $xNew = 1; |
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| 1099 | $dx = 1; |
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| 1100 | $i = 0; |
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| 1101 | ||
| 1102 | while ((abs($dx) > PRECISION) && ($i++ < MAX_ITERATIONS)) { |
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| 1103 | // Apply Newton-Raphson step |
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| 1104 | $result = self::CHIDIST($x, $degrees); |
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| 1105 | $error = $result - $probability; |
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| 1106 | if ($error == 0.0) { |
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| 1107 | $dx = 0; |
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| 1108 | } elseif ($error < 0.0) { |
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| 1109 | $xLo = $x; |
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| 1110 | } else { |
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| 1111 | $xHi = $x; |
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| 1112 | } |
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| 1113 | // Avoid division by zero |
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| 1114 | if ($result != 0.0) { |
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| 1115 | $dx = $error / $result; |
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| 1116 | $xNew = $x - $dx; |
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| 1117 | } |
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| 1118 | // If the NR fails to converge (which for example may be the |
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| 1119 | // case if the initial guess is too rough) we apply a bisection |
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| 1120 | // step to determine a more narrow interval around the root. |
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| 1121 | if (($xNew < $xLo) || ($xNew > $xHi) || ($result == 0.0)) { |
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| 1122 | $xNew = ($xLo + $xHi) / 2; |
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| 1123 | $dx = $xNew - $x; |
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| 1124 | } |
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| 1125 | $x = $xNew; |
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| 1126 | } |
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| 1127 | if ($i == MAX_ITERATIONS) { |
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| 1128 | return Functions::NA(); |
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| 1129 | } |
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| 1130 | ||
| 1131 | return round($x, 12); |
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| 1132 | } |
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| 1133 | ||
| 1134 | return Functions::VALUE(); |
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| 1135 | } |
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| 1136 | ||
| 1137 | /** |
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| 1138 | * CONFIDENCE. |
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| @@ 3462-3508 (lines=47) @@ | ||
| 3459 | * |
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| 3460 | * @return float |
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| 3461 | */ |
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| 3462 | public static function TINV($probability, $degrees) |
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| 3463 | { |
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| 3464 | $probability = Functions::flattenSingleValue($probability); |
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| 3465 | $degrees = floor(Functions::flattenSingleValue($degrees)); |
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| 3466 | ||
| 3467 | if ((is_numeric($probability)) && (is_numeric($degrees))) { |
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| 3468 | $xLo = 100; |
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| 3469 | $xHi = 0; |
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| 3470 | ||
| 3471 | $x = $xNew = 1; |
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| 3472 | $dx = 1; |
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| 3473 | $i = 0; |
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| 3474 | ||
| 3475 | while ((abs($dx) > PRECISION) && ($i++ < MAX_ITERATIONS)) { |
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| 3476 | // Apply Newton-Raphson step |
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| 3477 | $result = self::TDIST($x, $degrees, 2); |
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| 3478 | $error = $result - $probability; |
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| 3479 | if ($error == 0.0) { |
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| 3480 | $dx = 0; |
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| 3481 | } elseif ($error < 0.0) { |
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| 3482 | $xLo = $x; |
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| 3483 | } else { |
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| 3484 | $xHi = $x; |
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| 3485 | } |
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| 3486 | // Avoid division by zero |
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| 3487 | if ($result != 0.0) { |
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| 3488 | $dx = $error / $result; |
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| 3489 | $xNew = $x - $dx; |
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| 3490 | } |
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| 3491 | // If the NR fails to converge (which for example may be the |
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| 3492 | // case if the initial guess is too rough) we apply a bisection |
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| 3493 | // step to determine a more narrow interval around the root. |
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| 3494 | if (($xNew < $xLo) || ($xNew > $xHi) || ($result == 0.0)) { |
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| 3495 | $xNew = ($xLo + $xHi) / 2; |
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| 3496 | $dx = $xNew - $x; |
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| 3497 | } |
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| 3498 | $x = $xNew; |
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| 3499 | } |
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| 3500 | if ($i == MAX_ITERATIONS) { |
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| 3501 | return Functions::NA(); |
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| 3502 | } |
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| 3503 | ||
| 3504 | return round($x, 12); |
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| 3505 | } |
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| 3506 | ||
| 3507 | return Functions::VALUE(); |
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| 3508 | } |
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| 3509 | ||
| 3510 | /** |
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| 3511 | * TREND. |
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