September 2014
Intermediate to advanced
236 pages
4h 17m
Japanese
Content preview from Think Bayes ―プログラマのためのベイズ統計入門
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8.5
到着率を推定する
■
95
事前確率 x
事後確率 x
予測 y
時間（分）
図 8-3 xの事前及び事後確率とyの予測値
8.5
到着率を推定する
これまでの分析は、（
1
）運転間隔の分布、（
2
）乗客の到着率の
2
つはわかっていると
いう仮定に基づいていた。
2
番目の仮定はこの時点で外すことができる。
あなたがボストンに引っ越したばかりだと仮定すると、レッドラインの乗客の到着率
はわからない。
2
、
3
日通勤して、少なくとも定性的に、当て推量できるようになる。も
う少し頑張ると、
λ
を定量的に推定できる。
毎日、駅に到着したら、時刻と待っている乗客数（プラットフォームが大きすぎると
きには、サンプル領域を選べばよい）を記録するのである。それから、待ち時間と、待っ
ている間に新たに到着した乗客数を記録する。
5
日経てば、次のようなデータができる。
k1 y k2
-- --- --
17 4.6 9
22 1.0 0
96
■
8
章
観察者バイアス
23 1.4 4
18 5.4 12
4 5.8 11
ここで、
k1
は到着時に待っている乗客数、
y
はあなたの待ち時間（分）、
k2
は待って
いる間に到着した乗客数だ。
1
週間では、
18
分待っている間に、
36
人の乗客が到着したので、到着率は、毎分
2
人と推定できる。実用目的には、この推定で ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.