{"blog_title":"Ken-Chaos\u2019s Random Notes on R","categories":["Fundamentals of Time Series Analysis","stochastic process","time series analysis"],"blog_url":"https://chaos-r.hatenadiary.jp/","url":"https://chaos-r.hatenadiary.jp/entry/2026/01/16/103607","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/chaos_kiyono/20260116/20260116101345.png","height":"190","provider_name":"Hatena Blog","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fchaos-r.hatenadiary.jp%2Fentry%2F2026%2F01%2F16%2F103607\" title=\"What Is the Difference Between Weak Stationarity, Linearity, and Gaussianity? - 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>","type":"rich","provider_url":"https://hatena.blog","version":"1.0","width":"100%","title":"What Is the Difference Between Weak Stationarity, Linearity, and Gaussianity?","author_url":"https://blog.hatena.ne.jp/chaos_kiyono/","description":"Three Concepts Most Commonly Confused in Time Series Analysis In introductory textbooks and lectures on time series analysis, as well as in papers related to time series analysis, terms such as weak stationarity, linearity, and Gaussianity appear very frequently. However, as applications of time ser\u2026","published":"2026-01-16 10:36:07","author_name":"chaos_kiyono"}