1: In vcov.merMod(object, use.hessian = use.hessian) :
variance-covariance matrix computed from finite-difference Hessian is
not positive definite or contains NA values: falling back to var-cov estimated from RX
2: In vcov.merMod(object, correlation = correlation, sigm = sig) :
variance-covariance matrix computed from finite-difference Hessian is
not positive definite or contains NA values: falling back to var-cov estimated from RX
这是运行以下程序出来,大概提示应该是 方差协方差矩阵 那里出问题了,请问用nlemr()程序时,应该用什么选项来指定我要的方差协方差矩阵呢。
- library(Matrix)
- library(lme4)
- data1 <- read.csv(file.choose())
- head(data1)
- is.numeric(data1$X1)
- nform <- ~X1^a*X2^b
- nfun <- deriv(nform,namevec=c("a","b"),
- function.arg=c("X1","X2","a","b"))
- startvec <- c(a=1,b=0.1)
- nm1 <- nlmer(Y ~ nfun(X1,X2,a,b) ~ a|TREE,
- data = data1, start = startvec)
- summary(nm1)



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