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use stdlib gamma, use beta and binom instead of gamma.
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| <pre><code><span class="line" id="L1"><span class="tok-kw">const</span> std = <span class="tok-builtin">@import</span>(<span class="tok-str">"std"</span>);</span> | ||
| <span class="line" id="L2"></span> | ||
| <span class="line" id="L3"><span class="tok-kw">pub</span> <span class="tok-kw">fn</span> <span class="tok-fn">lbinomial</span>(n: <span class="tok-type">f64</span>, k: <span class="tok-type">f64</span>) <span class="tok-type">f64</span> {</span> | ||
| <span class="line" id="L4"> <span class="tok-kw">const</span> num = std.math.lgamma(<span class="tok-type">f64</span>, n + <span class="tok-number">1</span>);</span> | ||
| <span class="line" id="L5"> <span class="tok-kw">const</span> den1 = std.math.lgamma(<span class="tok-type">f64</span>, k + <span class="tok-number">1</span>);</span> | ||
| <span class="line" id="L6"> <span class="tok-kw">const</span> den2 = std.math.lgamma(<span class="tok-type">f64</span>, n - k + <span class="tok-number">1</span>);</span> | ||
| <span class="line" id="L7"> <span class="tok-kw">return</span> num - den1 - den2;</span> | ||
| <span class="line" id="L8">}</span> | ||
| <span class="line" id="L9"></span> | ||
| <span class="line" id="L10"><span class="tok-kw">pub</span> <span class="tok-kw">fn</span> <span class="tok-fn">binomial</span>(n: <span class="tok-type">f64</span>, k: <span class="tok-type">f64</span>) <span class="tok-type">f64</span> {</span> | ||
| <span class="line" id="L11"> <span class="tok-kw">return</span> <span class="tok-builtin">@exp</span>(lbinomial(n, k));</span> | ||
| <span class="line" id="L12">}</span> | ||
| <span class="line" id="L13"></span> | ||
| <span class="line" id="L14"><span class="tok-kw">pub</span> <span class="tok-kw">fn</span> <span class="tok-fn">lbeta</span>(a: <span class="tok-type">f64</span>, b: <span class="tok-type">f64</span>) <span class="tok-type">f64</span> {</span> | ||
| <span class="line" id="L15"> <span class="tok-kw">const</span> num1 = std.math.lgamma(<span class="tok-type">f64</span>, a);</span> | ||
| <span class="line" id="L16"> <span class="tok-kw">const</span> num2 = std.math.lgamma(<span class="tok-type">f64</span>, b);</span> | ||
| <span class="line" id="L17"> <span class="tok-kw">const</span> den = std.math.lgamma(<span class="tok-type">f64</span>, a + b);</span> | ||
| <span class="line" id="L18"> <span class="tok-kw">return</span> num1 + num2 - den;</span> | ||
| <span class="line" id="L19">}</span> | ||
| <span class="line" id="L20"></span> | ||
| <span class="line" id="L21"><span class="tok-kw">pub</span> <span class="tok-kw">fn</span> <span class="tok-fn">beta</span>(a: <span class="tok-type">f64</span>, b: <span class="tok-type">f64</span>) <span class="tok-type">f64</span> {</span> | ||
| <span class="line" id="L22"> <span class="tok-kw">return</span> <span class="tok-builtin">@exp</span>(lbeta(a, b));</span> | ||
| <span class="line" id="L23">}</span> | ||
| <span class="line" id="L24"></span> | ||
| </code></pre></body> | ||
| </html> |
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