<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bayesian Inference |</title><link>https://sichen-wang.github.io/tags/bayesian-inference/</link><atom:link href="https://sichen-wang.github.io/tags/bayesian-inference/index.xml" rel="self" type="application/rss+xml"/><description>Bayesian Inference</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 09 Apr 2024 16:43:16 +0000</lastBuildDate><image><url>https://sichen-wang.github.io/media/icon_hu_9dfcb674aa885f38.png</url><title>Bayesian Inference</title><link>https://sichen-wang.github.io/tags/bayesian-inference/</link></image><item><title>一类贝叶斯定理相关积分的变换技巧</title><link>https://sichen-wang.github.io/blog/%E4%B8%80%E7%B1%BB%E8%B4%9D%E5%8F%B6%E6%96%AF%E5%AE%9A%E7%90%86%E7%9B%B8%E5%85%B3%E7%A7%AF%E5%88%86%E7%9A%84%E5%8F%98%E6%8D%A2%E6%8A%80%E5%B7%A7/</link><pubDate>Tue, 09 Apr 2024 16:43:16 +0000</pubDate><guid>https://sichen-wang.github.io/blog/%E4%B8%80%E7%B1%BB%E8%B4%9D%E5%8F%B6%E6%96%AF%E5%AE%9A%E7%90%86%E7%9B%B8%E5%85%B3%E7%A7%AF%E5%88%86%E7%9A%84%E5%8F%98%E6%8D%A2%E6%8A%80%E5%B7%A7/</guid><description>&lt;p&gt;考虑非负实数域上某可用条件概率刻画的期望：&lt;/p&gt;
\[
E(x) = \int_{0}^{+\infty} xP(t = x|q) \mathrm{d}x
\]&lt;p&gt;其中 \(q\) 为已知，且 \(P(q|t = x)\) 是可用初等函数刻画的，于是：&lt;/p&gt;
&lt;p&gt;考虑贝叶斯定理：&lt;/p&gt;
\[
E(x) = \int_{0}^{+\infty} x\frac{P(q|t = x)P(t = x)}{P(q)} \mathrm{d}x
\]&lt;p&gt;观察发现对 \(x\) 微分本质上就是在枚举每个 \(t = x\) 的情况，于是 \(P(t = x)\) 已经被 \(\mathrm{d}x\) 包含，可以看作 \(1\)，故&lt;/p&gt;
\[
E(x) = \int_{0}^{+\infty} x\frac{P(q|t = x)}{P(q)} \mathrm{d}x
\]&lt;p&gt;大多数情况下，哪怕 \(P(q)\) 可以用初等函数刻画，整个式子也会难以化简，于是考虑拆 \(P(q)\)：&lt;/p&gt;
\[
E(x) = \int_{0}^{+\infty} x\frac{P(q|t = x)}{\int_{0}^{+\infty} P(q|t = y) \mathrm{d}y } \mathrm{d}x
\]&lt;p&gt;整理可得&lt;/p&gt;
\[
E(x) = \frac{\int_{0}^{+\infty} xP(q|t = x) \mathrm{d}x}{\int_{0}^{+\infty} P(q|t = x) \mathrm{d}x }
\]&lt;p&gt;设 \(P(q|t = x) = f(x)\)，其中 \(f(x)\) 是初等函数，又设 \(\delta\) 为积分算子（即 \([\delta f(x)]' = f(x)\) ），即得&lt;/p&gt;
\[
E(x) = \frac{\int_{0}^{+\infty} xf(x) \mathrm{d}x}{\int_{0}^{+\infty} f(x) \mathrm{d}x } = \lim_{\varepsilon \to 0^+}^{m \to +\infty}\frac{\delta mf(m) - \delta \varepsilon f(\varepsilon)}{\delta f(m) - \delta f(\varepsilon)}
\]</description></item></channel></rss>