{"type":"rich","categories":["SOBI","fractal","long-range correlation","stochastic process","time series analysis"],"html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fchaos-r.hatenadiary.jp%2Fentry%2F2026%2F01%2F22%2F235700\" title=\" Naive Second-Order Blind Identification\u2013based Oriented Fractal Scaling Component Analysis (SOBI-based OFSCA) - 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>","title":" Naive Second-Order Blind Identification\u2013based Oriented Fractal Scaling Component Analysis (SOBI-based OFSCA)","version":"1.0","author_url":"https://blog.hatena.ne.jp/chaos_kiyono/","blog_title":"Ken-Chaos\u2019s Random Notes on R","author_name":"chaos_kiyono","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/chaos_kiyono/20260122/20260122231417.png","blog_url":"https://chaos-r.hatenadiary.jp/","width":"100%","provider_name":"Hatena Blog","description":"Oriented Fractal Scaling Component Analysis (OFSCA) aims to decompose a two-dimensional (2D) trajectory into latent components that have distinct orientations and distinct fractal (scaling) properties. The original OFSCA framework detects orientations by scanning projection angles and finding direct\u2026","published":"2026-01-22 23:57:00","provider_url":"https://hatena.blog","height":"190","url":"https://chaos-r.hatenadiary.jp/entry/2026/01/22/235700"}