Full_Name: Jerome Asselin
Version: 1.6.1
OS: RedHat Linux 7.2
Submission from: (NULL) (142.103.173.179)
There is something very queer happening with the degrees
of freedom in nlme(). In the example below, I am fitting
the same model with lme() and nlme(). I am using the
nlme package version 3.1-34.
library(nlme)
set.seed(14)
a <- 2
x <- rep(rnorm(3),rep(5,3))
id <- rep(c("a","b","c"),rep(5,3))
y <- a+x+rnorm(15)
data <- data.frame(y=y,id=id)
initx <- matrix(x[c(1,6,11)],dimnames=list(c("a","b","c"),"x"))
summary(fit.lme <-
lme(y ~ 1,data=data,random=~1|id,method="ML"))
summary(fit.nlme <-
nlme(y ~ a + x, fixed= a~1, random=x~1|id,
data=data, start=list(fixed=c(a=2),
random=list(id=initx)),method="ML"))
The number of degrees of freedom for the intercept parameter
is 12 degrees using lme(), but only 2 degrees using nlme().
The same problem is noticed with seeds 15, 16 and 17.
But if I change the seed to 18 and try again, then I get 12
degrees of freedom for both lme() and nlme().
set.seed(18)
a <- 2
x <- rep(rnorm(3),rep(5,3))
id <- rep(c("a","b","c"),rep(5,3))
y <- a+x+rnorm(15)
data <- data.frame(y=y,id=id)
initx <- matrix(x[c(1,6,11)],dimnames=list(c("a","b","c"),"x"))
summary(fit.lme <-
lme(y ~ 1,data=data,random=~1|id,method="ML"))
summary(fit.nlme <-
nlme(y ~ a + x, fixed= a~1, random=x~1|id,
data=data, start=list(fixed=c(a=2),
random=list(id=initx)),method="ML"))
If I set the seed to 5 or 8, then nlme() fails despite the
simplicity of the model. The error messages are:
- for set.seed(5):
Step halving factor reduced below minimum in PNLS step
- for set.seed(8):
Singularity in backsolve at level 0, block 1
This issue of degrees of freedom may be related to the
convergence problems stated in another bug report (PR#2369).
Sincerely,
Jerome Asselin
set.seed(5)
a <- 2
x <- rep(rnorm(3),rep(5,3))
id <- rep(c("a","b","c"),rep(5,3))
y <- a+x+rnorm(15)
data <- data.frame(y=y,id=id)
initx <- matrix(x[c(1,6,11)],dimnames=list(c("a","b","c"),"x"))
summary(fit.lme <-
lme(y ~ 1,data=data,random=~1|id,method="ML"))
summary(fit.nlme <-
nlme(y ~ a + x, fixed= a~1, random=x~1|id,
data=data, start=list(fixed=c(a=2),
random=list(id=initx)),method="ML"))
set.seed(8)
a <- 2
x <- rep(rnorm(3),rep(5,3))
id <- rep(c("a","b","c"),rep(5,3))
y <- a+x+rnorm(15)
data <- data.frame(y=y,id=id)
initx <- matrix(x[c(1,6,11)],dimnames=list(c("a","b","c"),"x"))
summary(fit.lme <-
lme(y ~ 1,data=data,random=~1|id,method="ML"))
summary(fit.nlme <-
nlme(y ~ a + x, fixed= a~1, random=x~1|id,
data=data, start=list(fixed=c(a=2),
random=list(id=initx)),method="ML"))
______________________________________________
[EMAIL PROTECTED] mailing list
http://www.stat.math.ethz.ch/mailman/listinfo/r-devel
