From 3a3a4cba0fff70ea42fde19ef75b9c6ebe761181 Mon Sep 17 00:00:00 2001
From: Claude <noreply@anthropic.com>
Date: Wed, 30 Sep 2026 06:30:00 +0000
Subject: [PATCH] test: migrate `stats/base/dists/hypergeometric/kurtosis` to
 ULP-based assertions

Replace relative tolerance assertions with ULP difference assertions using
`@stdlib/assert/is-almost-same-value`. Both the JavaScript and C
implementations reproduce all 100 Julia fixture values exactly, so the
minimum required ULP bound is 0.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Rm5v6R5JFbwVZMqaYZWitD
---
 .../base/dists/hypergeometric/kurtosis/test/test.js | 13 ++-----------
 .../hypergeometric/kurtosis/test/test.native.js     | 13 ++-----------
 2 files changed, 4 insertions(+), 22 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.js
index 3498425dc416..70603c3f8ce9 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.js
@@ -21,10 +21,9 @@
 // MODULES //
 
 var tape = require( 'tape' );
+var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var kurtosis = require( './../lib' );
 
 
@@ -119,8 +118,6 @@ tape( 'if provided an `n` which is not a nonnegative integer, the function retur
 
 tape( 'the function returns the excess kurtosis of a hypergeometric distribution', function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var N;
 	var K;
 	var n;
@@ -133,13 +130,7 @@ tape( 'the function returns the excess kurtosis of a hypergeometric distribution
 	n = data.n;
 	for ( i = 0; i < n.length; i++ ) {
 		y = kurtosis( N[i], K[i], n[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'N: '+N[i]+', K: '+K[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 1.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. N: '+N[i]+'. K: '+K[i]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[ i ], 0 ), true, 'returns expected value' );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js
index 633228f2fd9e..7f8df34510ee 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
+var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // FIXTURES //
@@ -128,8 +127,6 @@ tape( 'if provided an `n` which is not a nonnegative integer, the function retur
 
 tape( 'the function returns the excess kurtosis of a hypergeometric distribution', opts, function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var N;
 	var K;
 	var n;
@@ -142,13 +139,7 @@ tape( 'the function returns the excess kurtosis of a hypergeometric distribution
 	n = data.n;
 	for ( i = 0; i < expected.length; i++ ) {
 		y = kurtosis( N[i], K[i], n[i] );
-		if ( y === expected[i] ) {
-			t.strictEqual( y, expected[i], 'N: '+N[i]+', K: '+K[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 1.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. N: '+N[i]+'. K: '+K[i]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.strictEqual( isAlmostSameValue( y, expected[ i ], 0 ), true, 'returns expected value' );
 	}
 	t.end();
 });