预测数据帧中的行数不等于馈送到预测函数的新数据帧中的行数

Question

我有一个基于因子向量拆分的数据框。我正在尝试为每个数据集创建一个模型，然后从中创建一组预测值。

我试图将预测值跨越大量值（例如 length.out = 500），但是当我向 predict 函数提供一个包含 500 行的新数据集时，它仍然吐出一个与输入模型的原始数据帧长度相同的预测数据帧。

data(mtcars)
rownames(mtcars) <- NULL #I've ran this code with and without this line, both times it gave the same result

mtcars.split <- split(mtcars, mtcars$cyl)

mtcars.split <- lapply(mtcars.split, function(x){
  rownames(x) <- NULL
  x <- droplevels(x)
  return(x)
})

mtcars.lm <- lapply(mtcars.split, function(x){
  lm(disp ~ wt, data = x)
})

mtcars.fitted <- mapply(x = mtcars.lm, y = mtcars.split, function(x, y){
  newdata = data.frame(wt = seq(min(y$wt), max(y$wt), length.out = 500))
  fitted <- as.data.frame(predict(x, new.data = newdata, se = T))
  return(fitted)
}, SIMPLIFY = F)

lapply(mtcars.fitted, nrow)
lapply(mtcars.split, nrow)

我尝试了运行整个数据集的线性模型，它做了同样的事情。

mtcars.lm.all <- lm(disp ~ wt, data = mtcars)
newdata <- data.frame(wt = seq(min(mtcars$wt), max(mtcars$wt), length.out = 500))
nrow(as.data.frame(predict(mtcars.lm.all, new.data = newdata, se = T)))

即使尝试对数据集进行子集化也没有任何区别。

mtcars.head <- head(mtcars, n = 16)
mtcars.head.lm <- lm(disp ~ wt, data = mtcars.head)
predict.mtcars <- as.data.frame(predict(mtcars.head.lm, 
                                        new.data = data.frame(wt = seq(min(mtcars.head$wt), 
                                                                       max(mtcars.head$wt), 
                                                                       length.out = 500)),
                                        se = T))
nrow(predict.mtcars)

我是不是漏掉了什么？这曾经有效，但现在似乎无效。即使重新启动 R 会话或我的计算机似乎也无法正常工作。

Answer 1

predict函数中的参数不是new.data而是newdata。

附上想要的结果。

data(mtcars)
rownames(mtcars) <- NULL #I've ran this code with and without this line, both times it gave the same result

mtcars.split <- split(mtcars, mtcars$cyl)

mtcars.split <- lapply(mtcars.split, function(x){
  rownames(x) <- NULL
  x <- droplevels(x)
  return(x)
})

mtcars.lm <- lapply(mtcars.split, function(x){
  lm(disp ~ wt, data = x)
})

mtcars.fitted <- mapply(x = mtcars.lm, y = mtcars.split, function(x, y){
  newdata = data.frame(wt = seq(min(y$wt), max(y$wt), length.out = 500))
  fitted <- as.data.frame(predict(x, newdata = newdata, se = T))
  return(fitted)
}, SIMPLIFY = F)

lapply(mtcars.fitted, nrow)
#> $`4`
#> [1] 500
#> 
#> $`6`
#> [1] 500
#> 
#> $`8`
#> [1] 500
lapply(mtcars.split, nrow)
#> $`4`
#> [1] 11
#> 
#> $`6`
#> [1] 7
#> 
#> $`8`
#> [1] 14


mtcars.lm.all <- lm(disp ~ wt, data = mtcars)
newdata <- data.frame(wt = seq(min(mtcars$wt), max(mtcars$wt), length.out = 500))
nrow(as.data.frame(predict(mtcars.lm.all, newdata = newdata, se = T)))
#> [1] 500

^{由 reprex package (v0.3.0)}

于 2020-07-22 创建

预测数据帧中的行数不等于馈送到预测函数的新数据帧中的行数

Number of rows in predicted data frame does not equal number of rows in new data frame fed to predict function

r

predict