October 2017
Intermediate to advanced
480 pages
9h 49m
Japanese
Content preview from Rではじめるデータサイエンス
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320
18
章
modelr
を使ったモデルの基本
#> <dbl> <dbl> <dbl>
#> 1 1 2 5
#> 2 1 1 6
このフォーミュラ表記は、「Wilkinson-Rogers表記」と呼ばれることもあり、G. N. Wilkinsonと
C. E. Rogersが「Symbolic Description of Factorial Models for Analysis of Variance」（http://bit.ly/
wilkrog）で最初に使いました。モデリング代数の詳細を理解するには、原論文を読むとよく、その
価値があります。
次節以降では、このフォーミュラ表記をどのようにカテゴリ変数、イテレーション、変換に使うか
を示します。
18.4.1
カテゴリ変数
フォーミュラから関数を生成するのは、予測子が連続なら簡単ですが、カテゴリ型なら面倒です。
y ~ sex
のようなフォーミュラだと想定し、
sex
が男性か女性かだとします。これを
y = x_0 + x_1
* sex
のような方程式に変換するのは、
sex
が数値ではないので乗算できず、意味をなしません。R
はその代わりに、
y = x_0 + x_1 * sex_male
に変換しておきます。ここで、
sex_male
は
sex
が男性
なら1、その他は 0です。
df <- tribble(
~ sex, ~ response,
"male", 1,
"female", 2,
"male", 1
)
model_matrix(df, response ...
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