August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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156
11 章 回帰
11.3
非線形関係
agepreg
の貢献が非線形かもしれないということを思い出してください。そのよう
な関係を捕捉する変数の追加を考えましょう。方法の
1
つとして、年齢の平方を含む
agepreg2
というカラムを作ることが挙げられます。
live['agepreg2'] = live.agepreg**2
formula ='totalwgt_lb ~ isfirst + agepreg + agepreg2'
さて、
agepreg
と
agepreg2
とのパラメータを推定することで、結果的に放物線を
適合させます。
Intercept 5.69 (1.38e-86)
isfirst[T.True] -0.0504 (0.109)
agepreg 0.112 (3.23e-07)
agepreg2 -0.00185 (8.8e-06)
R^2 0.007462
agepreg2
のパラメータは負で、放物線は下向きであり、図
10-2
の曲線に合致します。
agepreg
の
2
次モデルは、出生時体重の変動をより多く説明します。
isfirst
のパ
ラメータは、このモデルでは、さらに小さくなって、もはや統計的に有意ではありま
せん。
agepreg2
のように計算結果の変数の利用は、多項式やその他の関数をデータに適
合させるときによく使う方法です。この過程は、まだ線形回帰だと考えられます。そ
の理由は、ある変数が他の変数の非線形関数かどうかにはかかわらず、従属変数が説
明変数の線形関数だからです。
次の表は、これらの回帰の結果をまとめたものです。 ...
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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.