Question

我有一些与此相似的代码：

library(tidyverse)
library(broom)

df <- tribble(~group, ~set, ~x, ~y,
  0, "training", 1, 2,
  0, "training", 2, 4,
  0, "training", 4, 9,
  0, "training", 5, 9,
  0, "training", 15, 29,
  0, "training", 20, 42,
  0, "training", 21, 42,
  0, "training", 25, 49,
  0, "test", 10, NA,
)
df %>%
  filter(set == "training") %>%
  group_by(group) %>%
  do(pm = lm(y ~ x, data = .)) %>%
  left_join(df, ., by = "group")

所以我得到这样的东西：

  group      set    x     y     model   
  <dbl>  <chr>    <dbl> <dbl>  <list>  
1    0. training    1.    2. <S3: lm>
2    0. training    2.    4. <S3: lm>
3    0. training    4.    9. <S3: lm>
4    0. training    5.    9. <S3: lm>
5    0. training   15.   29. <S3: lm>
6    0. training   20.   42. <S3: lm>
7    0. training   21.   42. <S3: lm>
8    0. training   25.   49. <S3: lm>
9    0. test       10.   NA  <S3: lm>

在第 set 等于“ test”的第9行中，如何使用线性模型从 x 预测 y ？预先感谢您的帮助

Answer 1

在按“分组”分组后，我们可以基于同一行上的replace模型，根据NA输出的predict lm {y}中的library(dplyr) df %>% filter(set == "training") %>% group_by(group) %>% do(pm = lm(y ~ x, data = .)) %>% left_join(df, ., by = "group") %>% group_by(group) %>% mutate(y = replace(y, is.na(y), predict(pm[[1]], newdata = data.frame(x = x[set == "test"])))) # A tibble: 9 x 5 # Groups: group [1] # group set x y pm # <dbl> <chr> <dbl> <dbl> <list> #1 0 training 1 2 <lm> #2 0 training 2 4 <lm> #3 0 training 4 9 <lm> #4 0 training 5 9 <lm> #5 0 training 15 29 <lm> #6 0 training 20 42 <lm> #7 0 training 21 42 <lm> #8 0 training 25 49 <lm> #9 0 test 10 20.0 <lm>元素

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如何将预测函数用于以小节形式存储为列的线性模型

1 个答案: