Month と Day を単なる乱数にする airquality$Month <- rnorm(153) airquality$Day <- rnorm(153)
x <- lm( Ozone ~ Solar.R +Wind +Temp +Month +Day, data = airquality )
# 単なる乱数にかえた Month と Day は当然,除かれる stepAIC(x)
# この二つを残す stepAIC(x, scope = list(lower = ~ Month + Day))
x <- 1 if(x) print ("X") else print("Z") エラー: 予想外の 'else' です ( " else" の) x <- 1 { if(x) print ("X") else print("Z") } [1] "X"
> x <- 1:3 > # ラベルを加えない > cbind(x, 4:6, deparse.level = 0) [,1] [,2] [1,] 1 4 [2,] 2 5 [3,] 3 6 > # シンボルとして意味があればラベル化する(デフォルト) > cbind(x, 4:6, deparse.level = 1) x [1,] 1 4 [2,] 2 5 [3,] 3 6 > # シンボル以外(定数など)でもラベル化する > cbind(x, 4:6, deparse.level = 2) x 4:6 [1,] 1 4 [2,] 2 5 [3,] 3 6 >
$ ./configure --with-charset=utf8
There are two built-in themes. The default, \f{theme_gray}, uses a very light grey background with white gridlines. ... We can still see the gridlines to aid in the judgement of position ..., but they have little visual impact and we can easily ``tune'' them out. The grey background gives the plot a similar colour (in a typographical sense) to the remainder of the text, ensuring that the graphics fit in with the flow of a text without jumping out with a bright white background. Finally, the grey background creates a continuous field of colour which ensures that the plot is perceived as a single visual entity.
実は,ggplot2 のこのグラフも,最初はなじめないテーマ設定だなぁ,と感じていたが,慣れてきた今では,上の説明もなるほどと思う.
res2 <- docMatrix2("writers", pos = c("名詞","形容詞"), minFreq = 5) # 各行(ターム)の頻度合計を列に追加したデータフレームを作成する # あるいはオブジェクトを上書きしてしまう. # ついでに降順に並び替える z <- data.frame(term = rownames(res2)[ order(rowSums(res2), decreasing= T ) ] , sums = rowSums(res2)[order(rowSums(res2), decreasing = T )] ) # 頻度別の単語数は table(z$sums) # 頻度が100を超えるタームを抽出 z[z$sums > 100,] # Termが"の"の行を確認 res[rownames(res) == "の", ]
Bootrec /FixMbr
で復活させた.