{"image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/chaos_kiyono/20260124/20260124234452.png","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fchaos-r.hatenadiary.jp%2Fentry%2F2026%2F01%2F25%2F003946\" title=\"An Introduction to Savitzky\u2013Golay Filters (Part I): Smoothing, Differentiation, and Frequency Characteristics - Ken-Chaos\u2019s Random Notes on R\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_url":"https://chaos-r.hatenadiary.jp/","published":"2026-01-25 00:39:46","blog_title":"Ken-Chaos\u2019s Random Notes on R","description":"This time, I\u2019ll introduce the Savitzky\u2013Golay filter, which is one of the standard methods for smoothing jagged, bumpy, and noisy data. This filter has the attractive property of reducing noise while preserving key signal features\u2014especially the shape and height of peaks (see the figure below). Becau\u2026","author_name":"chaos_kiyono","version":"1.0","title":"An Introduction to Savitzky\u2013Golay Filters (Part I): Smoothing, Differentiation, and Frequency Characteristics","width":"100%","provider_url":"https://hatena.blog","type":"rich","author_url":"https://blog.hatena.ne.jp/chaos_kiyono/","provider_name":"Hatena Blog","url":"https://chaos-r.hatenadiary.jp/entry/2026/01/25/003946","categories":["Fundamentals of Digital Filters","Fundamentals and Applications of Savitzky\u2013Golay Filters","FIR filter","time series analysis","R"],"height":"190"}