r - 使用扫帚和tidyverse总结r平方的gams

Question

我发布了一个问题here，并能够重现Claus' answer，以便在虹膜数据上使用tidyverse为加性模型中的每个物种计算多个r平方值。但是，软件包发生了更新，现在尚未计算R-sq值。不知道为什么...
这是子句的响应和输出

library(tidyverse)
library(broom)
iris %>% nest(-Species) %>% 
  mutate(fit = map(data, ~mgcv::gam(Sepal.Width ~ s(Sepal.Length, bs = "cs"), data = .)),
         results = map(fit, glance),
         R.square = map(fit, ~ summary(.)$r.sq)) %>%
  unnest(results) %>%
  select(-data, -fit)

#      Species  R.square       df    logLik      AIC      BIC deviance df.residual
# 1     setosa 0.5363514 2.546009 -1.922197 10.93641 17.71646 3.161460    47.45399
# 2 versicolor 0.2680611 2.563623 -3.879391 14.88603 21.69976 3.418909    47.43638
# 3  virginica 0.1910916 2.278569 -7.895997 22.34913 28.61783 4.014793    47.72143

但是我的代码和输出使用 R.square <dbl [1]>值产生了此结果

library(tidyverse)
library(broom)
iris %>% nest(-Species) %>% 
  mutate(fit = map(data, ~mgcv::gam(Sepal.Width ~ s(Sepal.Length, bs = "cs"), data = .)),
          results = map(fit, glance),
          R.square = map(fit, ~ summary(.)$r.sq)) %>%
   unnest(results) %>%
   select(-data, -fit)

     Species  R.square       df    logLik      AIC      BIC deviance
      <fctr>    <list>    <dbl>     <dbl>    <dbl>    <dbl>    <dbl>
1     setosa <dbl [1]> 2.396547 -1.973593 10.74028 17.23456 3.167966
2 versicolor <dbl [1]> 2.317501 -4.021222 14.67745 21.02058 3.438361
3  virginica <dbl [1]> 2.278569 -7.895997 22.34913 28.61783 4.014793

谁能提供为什么的见解？

Answer 1

我和OP具有相同的sessionInfo(请参阅上面的注释)。我可以通过使用map_dbl强制R-squared为double来解决此问题。我不完全知道为什么它能按原样用于Akrun ...？

iris %>% nest(-Species) %>% 
  mutate(fit = map(data, ~mgcv::gam(Sepal.Width ~ s(Sepal.Length, bs = "cs"), data = .)),
         results = map(fit, glance),
         R.square = map_dbl(fit, ~ summary(.)$r.sq)) %>%
  unnest(results) %>%
  select(-data, -fit)

# A tibble: 3 x 8
  Species    R.square    df logLik   AIC   BIC deviance df.residual
  <fct>         <dbl> <dbl>  <dbl> <dbl> <dbl>    <dbl>       <dbl>
1 setosa        0.536  2.55  -1.92  10.9  17.7     3.16        47.5
2 versicolor    0.268  2.56  -3.88  14.9  21.7     3.42        47.4
3 virginica     0.191  2.28  -7.90  22.3  28.6     4.01        47.7