feat: initial implementation of stats/base/dists/halfnormal/cdf
#9429
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---
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stats/base/dists/halfnormal/cdf
kgryte
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| "@stdlib/math/base/assert/is-nan": "^0.2.2", | ||
| "@stdlib/math/base/special/erf": "^0.2.2", | ||
| "@stdlib/math/base/special/sqrt": "^0.2.2", | ||
| "@stdlib/stats/base/dists/degenerate/cdf": "^0.2.2", | ||
| "@stdlib/utils/constant-function": "^0.2.2", | ||
| "@stdlib/utils/define-nonenumerable-read-only-property": "^0.2.2" |
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| "@stdlib/math/base/assert/is-nan": "^0.2.2", | |
| "@stdlib/math/base/special/erf": "^0.2.2", | |
| "@stdlib/math/base/special/sqrt": "^0.2.2", | |
| "@stdlib/stats/base/dists/degenerate/cdf": "^0.2.2", | |
| "@stdlib/utils/constant-function": "^0.2.2", | |
| "@stdlib/utils/define-nonenumerable-read-only-property": "^0.2.2" |
kgryte
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| t.end(); | ||
| }); | ||
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| tape('if provided `x < mu`, the function returns `0`', function test(t) { |
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| tape('if provided `x < mu`, the function returns `0`', function test(t) { | |
| tape( 'if provided `x < mu`, the function returns `0`', function test( t ) { |
kgryte
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| t.equal(y, expected[i], 'x: ' + x[i] + ', mu: ' + mu[i] + ', sigma: ' + sigma[i] + ', y: ' + y + ', expected: ' + expected[i]); | ||
| } else { | ||
| del = abs(y - expected[i]); | ||
| t.ok(del <= 1e-14, 'within tolerance. x: ' + x[i] + '. y: ' + y + '. E: ' + expected[i] + '. Delt: ' + del); |
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| t.ok(del <= 1e-14, 'within tolerance. x: ' + x[i] + '. y: ' + y + '. E: ' + expected[i] + '. Delt: ' + del); | |
| t.ok(del <= 1e-14, 'within tolerance. x: ' + x[i] + '. y: ' + y + '. E: ' + expected[i] + '. Delt: ' + del); |
Use assert/is-almost-same-value with an appropriate maxULPs argument.
kgryte
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| * | ||
| * @example | ||
| * var y = cdf( 2.0, 0.0, 1.0 ); | ||
| * // returns 0.9544997361036416 |
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| * // returns 0.9544997361036416 | |
| * // returns ~0.9545 |
kgryte
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| ```javascript | ||
| var y = cdf( 2.0, 0.0, 1.0 ); | ||
| // returns 0.9544997361036416 |
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| // returns 0.9544997361036416 | |
| // returns ~0.9545 |
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type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
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Progresses #9416
Description
This pull request:
@stdlib/stats/base/dists/halfnormal/cdfpackage with complete functionality including:Related Issues
This pull request has the following related issues:
Questions
No.
Other
Implementation Notes:
The half-normal distribution CDF is implemented using the error function (erf):
where μ is the location parameter and σ is the scale parameter.
Package Structure:
The implementation closely mirrors the structure of
@stdlib/stats/base/dists/normal/cdfto ensure consistency across the stdlib codebase:lib/main.js- Main CDF implementationlib/factory.js- Factory function for partial applicationlib/index.js- Package exportstest/test.cdf.js- Comprehensive tests for the main functiontest/test.factory.js- Tests for the factory functiontest/test.js- Basic module testsexamples/index.js- Usage examplesbenchmark/benchmark.js- Performance benchmarksdocs/types/index.d.ts- TypeScript definitionsdocs/types/test.ts- TypeScript definition testsdocs/repl.txt- REPL documentationtest/fixtures/julia/- Test fixture generation scriptsChecklist
AI Assistance
If you answered "yes" above, how did you use AI assistance?
Disclosure
The tests and documentation were primarily authored by Claude Code, but the research and understanding of the half-normal distribution were done by me, and the CDF function's code implementation was entirely authored and reviewed by me.
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