R 运行 顺序回归
R Run Regressions In Sequence
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)
我想知道，如何使用某种函数 运行 所有这些回归？
基本上，回归在 COVS1 上回归 'alpha'，然后在 COVS1 和 COVS2 上回归 'alpha'，然后在 COVS1、COVS2 和 COVS3 上回归 'alpha'。这是针对整个数据完成的，然后分别针对 GROUP == 0 和 GROUP == 1 完成。重复相同的过程，将 'alpha' 替换为 'bravo' 然后 'charlie' 所以我只是希望 运行 所有这些，然后存储模型和系数估计以及所有输出的标准误差..
我们可以创建一个循环来执行此操作
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$resp[i])
tidy(lm(fmla, data = data))
}))
或者如果我们需要一个数据集
library(dplyr)
library(purrr)
out_dat <- lapply(seq_along(COVS), function(i)
map_dfr(seq_along(COVS), ~ {
fmla <- reformulate(c(df1$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
如果我们需要在数据的 subset 上应用 lm，则对数据进行子集化
dat0 <- subset(data, GROUP == 0)
dat1 <- subset(data, GROUP == 1)
并将 lm 中的 data 更改为 'dat0'、'dat1'
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)
我想知道，如何使用某种函数 运行 所有这些回归？ 基本上，回归在 COVS1 上回归 'alpha'，然后在 COVS1 和 COVS2 上回归 'alpha'，然后在 COVS1、COVS2 和 COVS3 上回归 'alpha'。这是针对整个数据完成的，然后分别针对 GROUP == 0 和 GROUP == 1 完成。重复相同的过程，将 'alpha' 替换为 'bravo' 然后 'charlie' 所以我只是希望 运行 所有这些，然后存储模型和系数估计以及所有输出的标准误差..
我们可以创建一个循环来执行此操作
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$resp[i])
tidy(lm(fmla, data = data))
}))
或者如果我们需要一个数据集
library(dplyr)
library(purrr)
out_dat <- lapply(seq_along(COVS), function(i)
map_dfr(seq_along(COVS), ~ {
fmla <- reformulate(c(df1$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
如果我们需要在数据的 subset 上应用 lm，则对数据进行子集化
dat0 <- subset(data, GROUP == 0)
dat1 <- subset(data, GROUP == 1)
并将 lm 中的 data 更改为 'dat0'、'dat1'