#r #data.table #sapply #mapply
#r #data.table #sapply #Отображение
Вопрос:
set.seed(1)
data=data.frame(
student=1:5000,
alfa =runif(5000),
bravo =runif(5000),
charlie =runif(5000),
delta =runif(5000),
echo =runif(5000),
foxtrot =runif(5000),
golf =runif(5000),
hotel =runif(5000),
india =runif(5000),
juliett =runif(5000),
kilo =runif(5000),
lima =runif(5000),
mike =runif(5000),
november =runif(5000),
oscar =runif(5000),
papa =runif(5000),
GROUP = sample(0:1, r=T))
##########################
COVS1 = c(golf, hotel, india)
COVS2 = c(juliett, kilo)
COVS3 = c(lima, mike, november, oscar, papa)
## OVERALL
lm(alpha ~ delta golf hotel india, data = data)
lm(alpha ~ delta golf hotel india juliett kilo, data = data)
lm(alpha ~ delta golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(alpha ~ echo golf hotel india, data = data)
lm(alpha ~ echo golf hotel india juliett kilo, data = data)
lm(alpha ~ echo golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(alpha ~ foxtrot golf hotel india, data = data)
lm(alpha ~ foxtrot golf hotel india juliett kilo, data = data)
lm(alpha ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(bravo ~ delta golf hotel india, data = data)
lm(bravo ~ delta golf hotel india juliett kilo, data = data)
lm(bravo ~ delta golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(bravo ~ echo golf hotel india, data = data)
lm(bravo ~ echo golf hotel india juliett kilo, data = data)
lm(bravo ~ echo golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(bravo ~ foxtrot golf hotel india, data = data)
lm(bravo ~ foxtrot golf hotel india juliett kilo, data = data)
lm(bravo ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(charlie ~ delta golf hotel india, data = data)
lm(charlie ~ delta golf hotel india juliett kilo, data = data)
lm(charlie ~ delta golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(charlie ~ echo golf hotel india, data = data)
lm(charlie ~ echo golf hotel india juliett kilo, data = data)
lm(charlie ~ echo golf hotel india juliett kilo lima mike november oscar papa, data = data)
lm(charlie ~ foxtrot golf hotel india, data = data)
lm(charlie ~ foxtrot golf hotel india juliett kilo, data = data)
lm(charlie ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data = data)
## GROUP == 0
lm(alpha ~ delta golf hotel india, data ~ subset(data, GROUP == 0)
lm(alpha ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(alpha ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(alpha ~ echo golf hotel india, data ~ subset(data, GROUP == 0)
lm(alpha ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(alpha ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(alpha ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 0)
lm(alpha ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(alpha ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(bravo ~ delta golf hotel india, data ~ subset(data, GROUP == 0)
lm(bravo ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(bravo ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(bravo ~ echo golf hotel india, data ~ subset(data, GROUP == 0)
lm(bravo ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(bravo ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(bravo ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 0)
lm(bravo ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(bravo ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(charlie ~ delta golf hotel india, data ~ subset(data, GROUP == 0)
lm(charlie ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(charlie ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(charlie ~ echo golf hotel india, data ~ subset(data, GROUP == 0)
lm(charlie ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(charlie ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
lm(charlie ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 0)
lm(charlie ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 0)
lm(charlie ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 0)
## GROUP == 1
lm(alpha ~ delta golf hotel india, data ~ subset(data, GROUP == 1)
lm(alpha ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(alpha ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(alpha ~ echo golf hotel india, data ~ subset(data, GROUP == 1)
lm(alpha ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(alpha ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(alpha ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 1)
lm(alpha ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(alpha ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(bravo ~ delta golf hotel india, data ~ subset(data, GROUP == 1)
lm(bravo ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(bravo ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(bravo ~ echo golf hotel india, data ~ subset(data, GROUP == 1)
lm(bravo ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(bravo ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(bravo ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 1)
lm(bravo ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(bravo ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(charlie ~ delta golf hotel india, data ~ subset(data, GROUP == 1)
lm(charlie ~ delta golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(charlie ~ delta golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(charlie ~ echo golf hotel india, data ~ subset(data, GROUP == 1)
lm(charlie ~ echo golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(charlie ~ echo golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
lm(charlie ~ foxtrot golf hotel india, data ~ subset(data, GROUP == 1)
lm(charlie ~ foxtrot golf hotel india juliett kilo, data ~ subset(data, GROUP == 1)
lm(charlie ~ foxtrot golf hotel india juliett kilo lima mike november oscar papa, data ~ subset(data, GROUP == 1)
Мне интересно, как можно запустить все эти регрессии, используя какую-то функцию?
В основном регрессии регрессируют «альфа» на COVS1, затем «альфа» на COVS1 и COVS2, а затем «альфа» на COVS1 и COVS2 и COVS3. Это делается для всех данных, а затем отдельно для GROUP == 0 и GROUP == 1. Повторяется тот же процесс, когда вы заменяете ‘alpha’ на ‘bravo’, а затем ‘charlie’, поэтому я просто хочу запустить все это, затем сохранить оценки модели и коэффициентов и стандартные ошибки для всех выходных данных..
Комментарии:
1. @akrun да, это переменные ответа
Ответ №1:
Мы могли бы создать цикл для этого
COVS1 <- c('golf', 'hotel', 'india')
COVS2 <- c('juliett', 'kilo')
COVS3 <- c('lima', 'mike', 'november', 'oscar', 'papa')
COVS <- list(COVS1, COVS2, COVS3)
df1 <- expand.grid(resp = c('alfa', 'bravo', 'charlie'),
pred = c('delta', 'echo', 'foxtrot'), stringsAsFactors = FALSE)
df1 <- df1[order(df1$resp),]
library(broom)
lst_mod <- lapply(seq_along(COVS), function(i)
lapply(seq_along(COVS), function(j) {
fmla <- reformulate(c(df1$pred[i], unlist(COVS[seq_len(j)])),
response = df1$resp[i])
tidy(lm(fmla, data = data))
}))
Или, если нам нужен один набор данных
library(dplyr)
library(purrr)
out_dat <- lapply(seq_along(COVS), function(i)
map_dfr(seq_along(COVS), ~ {
fmla <- reformulate(c(df1$pred[i], unlist(COVS[seq_len(.x)])),
response = df1$resp[i])
tidy(lm(fmla, data = data)) %>%
mutate(response_variable = df1$resp[i], formula = list(fmla))
})) %>%
bind_rows
Если нам нужно применить lm к subset данным, подмножество данных
dat0 <- subset(data, GROUP == 0)
dat1 <- subset(data, GROUP == 1)
и измените data in lm на ‘dat0’, ‘dat1’
Комментарии:
1. я думаю, что это на самом деле идеально, спасибо вам!!! теперь как насчет извлечения coef и стандартной ошибки в data.table, чтобы я мог видеть, из какой модели и коэффициента она взята???
2. @bvowe вы можете обернуть
tidylmобъект (изbroom), чтобы получить его в виде таблицы. Обновлено3. @bvowe конечно, дайте мне знать, когда будете в Сети
4. @bvowe извините, сейчас я немного занят. будет говорить через два часа
5. @bvowe Привет, ты здесь