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在带有偏移项的glm上使用broom(增强)和modelr(crossv_kfold)时出错

modelr broom glm offset r

2

Bart Spoon · 技术社区 · 8 年前

library(tidyverse)
library(modelr)
non_breaks = rpois(dim(warpbreaks)[1],20)
warp = warpbreaks %>%
    mutate(total = breaks + non_breaks)

library(broom)
warp_no_offset = crossv_kfold(warp, k = 10) %>%
    mutate(model = map(train, ~ glm(breaks~ wool*tension, ., family=poisson))) %>%
    mutate(predicted = map2(model, test, ~ augment(.x, newdata = .y, predict.type= "response")))

warp_offset = crossv_kfold(warp, k = 10) %>%
    mutate(model = map(train, ~ glm(breaks~ offset(log(total)) + wool*tension, ., family=poisson))) %>%
    mutate(predicted = map2(model, test, ~ augment(.x, newdata = .y, predict.type= "response")))

它抛出了一个错误:

Error in mutate_impl(.data, dots) : 
    Evaluation error: arguments imply differing number of rows: 5, 49.

1 回复 | 直到 8 年前

1

Hack-R 8 年前

offset() 没有被评估你认为是如何和何时。我知道这很棘手,但解决办法很简单。

你只需要记住使用 I()

例如:

warp_offset = crossv_kfold(warp, k = 10) %>%
  mutate(model = map(train, ~ glm(breaks~ I(offset(log(total))) + wool*tension, ., family=poisson))) %>%
  mutate(predicted = map2(model, test, ~ augment(.x, newdata = .y, predict.type= "response")))