# 隨機微積分 :::success [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) ::: :::info 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> ::: [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)