我一直在使用下面的代码成功修改使用lme4版本<1.0的模型的'Zt','L'和'A'插槽。我今天刚刚更新到lme4 1.0-4,发现模型对象不同。任何人都可以提供有关如何在新的lmer模型对象中修改这些插槽的见解/指导吗?
dat<-structure(list(pop1 = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 10L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L,
7L, 8L, 8L, 9L), pop2 = c(2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 1L,
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
5L, 6L, 7L, 8L, 9L, 10L, 6L, 7L, 8L, 9L, 10L, 7L, 8L, 9L, 10L,
8L, 9L, 10L, 9L, 10L, 10L), X = c(0.49136, 0.75587, 0.93952,
0.61278, 0.79934, 1.07918, 1.13354, 1.15836, 1.2014, 0.43136,
0.77815, 0.716, 0.93952, 1.13672, 1.16137, 1.18184, 1.21748,
0.65321, 0.86332, 1.04922, 1.19866, 1.20412, 1.22272, 1.24797,
0.89763, 1.08991, 1.19033, 1.15836, 1.17319, 1.18752, 0.64345,
0.93952, 0.98227, 1.01703, 1.07188, 0.78533, 0.94939, 0.99564,
1.06819, 0.64345, 0.716, 0.85126, -0.04576, 0.4624, 0.30103),
Y = c(0.491694, 0.394703, 0.113303, 0.156597, 0.450924, 0.487845,
0.21821, 0.129027, -0.131522, 0.35156, -0.116826, 0.18941,
0.306608, 0.258401, 0.008552, -0.024369, -0.305258, -0.013628,
0.215715, 0.13783, 0.467272, 0.088882, 0.084295, -0.172337,
-0.206725, -0.084339, -0.191651, -0.001586, -0.079501, -0.195094,
0.232045, 0.17102, 0.003742, -0.023688, -0.26085, 0.205326,
0.172809, 0.133219, -0.159054, 0.082231, 0.011025, -0.238611,
0.732679, 0.478058, 0.325698)), .Names = c("pop1", "pop2",
"X", "Y"), class = "data.frame", row.names = c(NA, -45L))
library(lme4) # lme4 versions >1.0 have different model output
# Specify the model formula
lmer_mod <- as.formula("Y ~ X + (1|pop1)")
# Create the Zl and ZZ matrices
Zl <- lapply(c("pop1","pop2"), function(nm) Matrix:::fac2sparse(dat[[nm]], "d", drop=FALSE))
ZZ <- Reduce("+", Zl[-1], Zl[[1]])
# Fit lmer model to the data
mod <- lmer(lmer_mod, data = dat, REML = TRUE)
# Replace the following slots in the fitted model
# These slots don't exist in this form in the new lmerMod objects
mod@Zt <- ZZ
mod@A <- ZZ
mod@L <- Cholesky(tcrossprod(ZZ), LDL=FALSE, Imult=1)
# Refit the model to the same response data
Final.mod <- refit(mod, dat[,Y])
非常感谢有关如何修改这些插槽的任何帮助或见解。与此同时,我想我会坚持使用旧版本的lme4来制作这些模型。
答案 0 :(得分:1)
这样做你想要的吗? (这跟?modular
非常接近......)
创建Zl和ZZ矩阵:
Zl <- lapply(c("pop1","pop2"),
function(nm) Matrix:::fac2sparse(dat[[nm]], "d", drop=FALSE))
ZZ <- Reduce("+", Zl[-1], Zl[[1]])
构造随机效应数据结构:
lf <- lFormula(Y ~ X + (1|pop1), data=dat)
修改它们:
lf$reTrms$Zt <- ZZ
继续完成剩余的模型构造和装配步骤:
dfun <- do.call(mkLmerDevfun,lf) ## create dev fun from modified lf
opt <- optimizeLmer(dfun) ## fit the model
## make the results into a 'merMod' object
fit <- mkMerMod(environment(dfun), opt, lf$reTrms,
fr = lf$fr)