{"html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fryamada22.hatenablog.jp%2Fentry%2F20150510%2F1431238218\" title=\"\u88dc\u907a\u3000\u78ba\u7387\u5909\u6570\u306e\u4e0d\u7b49\u5f0f - ryamada\u306e\u907a\u4f1d\u5b66\u30fb\u907a\u4f1d\u7d71\u8a08\u5b66\u30e1\u30e2\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_url":"https://hatena.blog","categories":["sublinear algorithm","Markov \u4e0d\u7b49\u5f0f","Chebychev \u4e0d\u7b49\u5f0f","Chernoff bound"],"author_name":"ryamada22","url":"https://ryamada22.hatenablog.jp/entry/20150510/1431238218","published":"2015-05-10 15:10:18","version":"1.0","title":"\u88dc\u907a\u3000\u78ba\u7387\u5909\u6570\u306e\u4e0d\u7b49\u5f0f","type":"rich","description":"Markov \u4e0d\u7b49\u5f0f \u3042\u308b\u78ba\u7387\u5909\u6570X\u306e\u5024\u304ct\u4ee5\u4e0a\u306b\u306a\u308b\u78ba\u7387\u306f\u3001X\u306e\u671f\u5f85\u5024\u3092t\u3067\u5272\u3063\u305f\u5024\u4ee5\u4e0b\u3067\u3042\u308b # \u53d6\u308a\u3046\u308b\u5024\u306e\u7a2e\u985e\u6570 n.val <- 10 # \u6b63\u306e\u78ba\u7387\u5909\u6570\u5024 v <- sort(runif(n.val)) library(MCMCpack) # \u5024\u5225\u306e\u751f\u8d77\u78ba\u7387 p <- rdirichlet(1,rep(1,n.val)) # \u671f\u5f85\u5024 Ex <- sum(v*p) Ex # \u78ba\u7387\u5909\u6570\u304c\u5024t[i]\u4ee5\u4e0a\u306b\u306a\u308b\u78ba\u7387\u306f\uff1f ts <- seq(from=min(v),to=max(v),length=100) # Markov \u4e0d\u7b49\u5f0f\u304c\u793a\u3059\u4e0a\u9650 PrMarkov <- Ex/ts plot(ts\u2026","blog_title":"ryamada\u306e\u907a\u4f1d\u5b66\u30fb\u907a\u4f1d\u7d71\u8a08\u5b66\u30e1\u30e2","blog_url":"https://ryamada22.hatenablog.jp/","height":"190","provider_name":"Hatena Blog","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/r/ryamada22/20150511/20150511141535.png","author_url":"https://blog.hatena.ne.jp/ryamada22/","width":"100%"}