r中多元混合模型的相关性

Question

我使用nlme包在R中运行多变量混合模型。假设x和y是纵向数据的响应变量，假设组内的误差是相关的。剩余误差矩阵表示为：

所以我的问题是如何将相关性纳入lme函数？ 我尝试过命令corr = corComSymm(from =~ 1 | x)或corr = corAR1(from =~ 1 | x)但是没有用！

这里是例子：

# visiting time by months
time = rep(c(0,3,6,9),time = 4, 200)
# subjects 
subject = rep(1:50, each = 4)
# first  response variable "identity"
x = c(rep(0, 100), rep(1,100)) 
# second  response variable "identity"
y = c(rep(1, 100), rep(0,100))
# values of both reponses variables (x_1, x_2)
value = c(rnorm(100,20,1),rnorm(100,48,1))
# variables refer to reponses variables (x_1, x_2)
variable = factor(c(rep(0,150),rep(1,50)), label=c("X","Y"))

df = data.frame(subject , time, x,y,value, variable)

library(nlme)
# fit the model that each response variable has intercept and slope (time) for each random and fixed effects
# as well as fixed effects slopes for sex and lesion, and each response has different variance 
f=  lme(value ~ -1 + x + y + x:time + y:time , random = ~ -1 + (x + y) + time:( x + y)|subject , 
       weights = varIdent(form=~1| x),corr = corAR1(from = ~ 1|x), control=lmeControl(opt="optim"), data =df)
Error in corAR1(from = ~1 | x) : unused argument (from = ~1 | x)

有什么建议吗？

Answer 1

我发现这个网站（下面）有用且有用，我在这里发布以防万一将来可能有这个问题。 https://rpubs.com/bbolker/3336