这是gamm()
使用数据集输入相关随机截距和斜率效应的语法sleepstudy
。
library(nlme)
library(mgcv)
data(sleepstudy,package='lme4')
# Model via lme()
fm1 <- lme(Reaction ~ Days, random= ~1+Days|Subject, data=sleepstudy, method='REML')
# Model via gamm()
fm1.gamm <- gamm(Reaction ~ Days, random= list(Subject=~1+Days), data=sleepstudy, method='REML')
VarCorr(fm1)
VarCorr(fm1.gamm$lme)
# Both are identical
# Subject = pdLogChol(1 + Days)
# Variance StdDev Corr
# (Intercept) 612.0795 24.740241 (Intr)
# Days 35.0713 5.922103 0.066
# Residual 654.9424 25.591843
输入不相关随机截距和斜率效应的语法对于 和 是相同lme()
的gamm()
。
# Model via lme()
fm2 <- lme(Reaction ~ Days, random= list(Subject=~1, Subject=~0+Days), data=sleepstudy, method='REML')
# Model via gamm()
fm2.gamm <- gamm(Reaction ~ Days, random= list(Subject=~1, Subject=~0+Days), data=sleepstudy, method='REML')
VarCorr(fm2)
VarCorr(fm2.gamm$lme)
# Both are identical
# Variance StdDev
# Subject = pdLogChol(1)
# (Intercept) 627.5690 25.051328
# Subject = pdLogChol(0 + Days)
# Days 35.8582 5.988172
# Residual 653.5838 25.565285
此答案还显示了如何将多个随机效果输入到lme()
.