R:正确调用包含 `i` 的变量

R: Correctly calling a variable that contains `i`

我正在使用 R 编程语言。我有以下创建 100 个数据集的代码(包含一个固定组件和一个随机组件):

a = rnorm(300,10,5)
b = rnorm(300,3,1)
c = rnorm(300,12,1)
e = "original"
d = data.frame(a,b,c,e)


results <- list()

for (i in 1:100){

a = rnorm(100,10,10)
b = rnorm(100,10,10)
c = rnorm(100,10,10)
e = "simulated"

d_i = data.frame(a,b,c,e)

data_i = rbind(d, d_i)
data_i$iteration = i
 results[[i]] <- data_i

}



results_df <- do.call(rbind.data.frame, results)

目前,这100个数据集已经全部放在了同一个文件中(“results_df”)。现在,我想将“results_df”文件分成这 100 个数据集(使用“迭代”列作为索引):

results_df$iteration = as.factor(results_df$iteration)
X<-split(results_df, results_df$iteration)

这个“X”文件似乎是一个“列表”,其中列出了 100 个数据集,每个数据集如下:

我可以通过使用 i 调用“索引”来访问这些文件中的每一个,例如

> head(X$`1`)
          a        b        c        e iteration
1  2.141495 3.984072 12.73344 original         1
2  8.769269 4.267464 11.32566 original         1
3  5.413573 2.823608 12.06713 original         1
4 11.710470 3.710500 12.20715 original         1
5 14.423155 2.944178 10.56673 original         1
6  6.886629 2.843195 12.43074 original         1
> head(X$`2`)
            a        b        c        e iteration
401  2.141495 3.984072 12.73344 original         2
402  8.769269 4.267464 11.32566 original         2
403  5.413573 2.823608 12.06713 original         2
404 11.710470 3.710500 12.20715 original         2
405 14.423155 2.944178 10.56673 original         2
406  6.886629 2.843195 12.43074 original         2
> head(X$`98`)
              a        b        c        e iteration
38801  2.141495 3.984072 12.73344 original        98
38802  8.769269 4.267464 11.32566 original        98
38803  5.413573 2.823608 12.06713 original        98
38804 11.710470 3.710500 12.20715 original        98
38805 14.423155 2.944178 10.56673 original        98
38806  6.886629 2.843195 12.43074 original        98

我的问题:我现在想编写另一个函数,对这 100 个数据集的每一个执行线性回归,保存回归系数,并将它们放入一个文件中。我试着为此编写代码:

results_1 <- list()

for (i in 1:100){

model_i <- lm(a ~ b +c, data = X$`i`)
coeff_i = model_i$coefficients

 results_1[[i]] <- coeff_i 

}

results_df_1 <- do.call(rbind.data.frame, results_1)

乍一看,这似乎有效 - 但它显示的所有回归系数都相同。这是不可能的,因为回归模型在不同数据集上 运行 100 次:

#for some reason, the column names have been corrupted

hist(results_df_1$c.14.5741211250235..14.5741211250235..14.5741211250235..14.5741211250235.., main = "first coeff")

 hist(results_df_1$c..0.105285805666629...0.105285805666629...0.105285805666629.., main = "second coeff")

 hist(results_df_1$c..0.236548691738492...0.236548691738492...0.236548691738492.., main = "third coeff")

有人可以帮我解决这个问题吗? 当您在 R 中使用“split()”函数时,这是在以后的命令中“调用”“拆分组件”的正确方法吗?

model_i <- lm(a ~ b +c, data = X$`i`)

谢谢!

我能够解决这个问题:

a = rnorm(300,10,5)
b = rnorm(300,3,1)
c = rnorm(300,12,1)
e = "original"
d = data.frame(a,b,c,e)


results <- list()

for (i in 1:100){

a = rnorm(100,10,10)
b = rnorm(100,10,10)
c = rnorm(100,10,10)
e = "simulated"

d_i = data.frame(a,b,c,e)

data_i = rbind(d, d_i)
data_i$iteration = i
 results[[i]] <- data_i

}



results_df <- do.call(rbind.data.frame, results)

X<-split(results_df, results_df$iteration)

#####

results_1 <- list()

for (i in 1:100){

#here was the problem
model_i <- lm(a ~ b +c, data = X[[i]])

coeff_i = model_i$coefficients

 results_1[[i]] <- model_i$coefficients

}

results_df_1 <- do.call(rbind.data.frame, results_1)

par(mfrow = c(1, 3))

hist(results_df_1[,1], main = "first coeff")
hist(results_df_1[,2], main = "second coeff")
hist(results_df_1[,3], main = "third coeff")