R线性回归中roll_lm和lm的差异_R

R线性回归中roll_lm和lm的差异

R线性回归中roll_lm和lm的差异,r,R,我想做一个滚动线性回归，我找到了函数roll_lm，但它提供了与函数lm不同的结果。难道它们不应该产生相同的结果吗 # creating dataset set.seed(123) ABC <- sample(seq(from = 20, to = 50, by = 5), size = 50, replace = TRUE) DCE <- sample(seq(from = 20, to = 50, by = 5), size = 50, replace = TRUE) # Ca

我想做一个滚动线性回归，我找到了函数roll_lm，但它提供了与函数lm不同的结果。难道它们不应该产生相同的结果吗

# creating dataset
set.seed(123)
ABC <- sample(seq(from = 20, to = 50, by = 5), size = 50, replace = TRUE)
DCE <- sample(seq(from = 20, to = 50, by = 5), size = 50, replace = TRUE)

# Calculating rolling correlation and using last coeff
library(roll)
Rolling.Correl <- roll_lm(ABC , DCE, 50)
last(Rolling.Correl$coefficients[,2])
# [1] -0.233245

# Calculating basic regression using lm
Trad.Rolling.Correl <- lm(ABC ~ DCE)
Trad.Rolling.Correl

# Call:
# lm(formula = ABC ~ DCE)
#
# Coefficients:
# (Intercept)          DCE  
#     41.9204      -0.2112

#创建数据集
种子集（123）
ABC？roll_lm
表示roll_lm（x，y，…）
，因此您需要将其与lm（DCE~ABC）

lm(formula = DCE ~ ABC)

# Coefficients:
# (Intercept)          ABC  
#     43.6236      -0.2332