# 隨機微積分
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[回筆記目錄](https://hackmd.io/68GUUX4MQXGXroA5TlsZ-Q)
編輯:2023/04/09 第二章施工中
[github](https://github.com/Iofting1023/2024-Spring--Introduction-to-stochastic-calculus)
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The spirit of stochastic calculus in general:
- *From a well-understood underlying source of randomness (usually a Brownian motion), what can we say about the distribution of a process that is constructed from it?*
<blockquote style="text-align: right;">
Louis-Pierre Arguin
</blockquote>
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[TOC]
## CH1 Basic Notions of Probability
1. 展示如何抽樣並畫出pdf, cdf, 以及對隨機變數做映射.
2. 透過計算樣本平均演示 強大數法則 和弱大數法則
3. 透過展示樣本平均的分佈,展示 中央極限定理
4. 先使用反函數法對柯西分佈做抽樣,並且展示在期望值不存在的狀況下,兩種大數法則皆會失效
- [數值習題連結](/unFH0uarTIiyYAHm-fAseQ)
## CH2 Gaussian Processes
- [章節重點](/aXhGsjnlQqeVH1kJy2c5nw)
- [數值習題連結](/S86a-OyYTTaKcOsvHH7IAA)