如何使用 r 提取分段包生成的斜率和截距变量并将其放入数据框中？

Question

谁能告诉我如何将分段包产生的斜率和截距取出并放入数据框中？这最终将用于将斜率和截距排列回其原始值。请参阅下面的数据（我从另一个 post 获取的数据）。

#加载包图书馆（分段）图书馆（整洁宇宙）

#set seed and develop data
set.seed(1)
Y<-c(13,21,12,11,16,9,7,5,8,8)
X<-c(74,81,80,79,89,96,69,88,53,72)
age<-c(50.45194,54.89382,46.52569,44.84934,53.25541,60.16029,50.33870,
   51.44643,38.20279,59.76469)
dat=data.frame(Y=Y,off.set.term=log(X),age=age)

#run initial GLM
glm.fit=glm(Y~age+off.set.term,data=dat,family=poisson)
summary(glm.fit)

#run segmented glm
glm.fitted.segmented <- segmented(glm.fit, seg.Z=~age + off.set.term, psi = 
list(age = c(50,53), off.set.term = c(4.369448)))

#Get summary, slopes and intercepts
summary(glm.fitted.segmented)
slope(glm.fitted.segmented)
intercept(glm.fitted.segmented)

Answer 1

library(broom)
library(dplyr)
library(tidyr)
library(stringr)

slopes <-
  bind_rows(lapply(slope(glm.fitted.segmented), tidy), .id = "variable") %>%
  mutate(type = str_extract(.rownames, "^[a-z]+"),
         model = str_extract(.rownames, "[0-9]+$")) %>%
  select(variable, model, type, estimate = "Est.")
intercepts <-
  bind_rows(lapply(intercept(glm.fitted.segmented), tidy), .id = "variable") %>%
  mutate(type = str_extract(.rownames, "^[a-z]+"),
         model = str_extract(.rownames, "[0-9]+$")) %>%
  select(variable, model, type, estimate = "Est.")

bind_rows(slopes, intercepts) %>%
  spread(type, estimate)

使用tidy函数，您可以轻松地提取每个变量的data.frame，然后提取单元的型号和类型。将它们全部绑定在一起并将类型和估计值展开以以变量、模型、截距和斜率结尾。

如何使用 r 提取分段包生成的斜率和截距变量并将其放入数据框中？

How can I pull slope and intercept variables produced by the segmented package and put into a dataframe using r?

r

piecewise