I have a mixed model with a non-linear term, so I would like to use the R package nlme
instead of lme
. However, switching to nlme
, even without adding anything to the model, causes Rstudio and R to crash.
I have found that even generated data, which can easily be fitted using lme
, causes this behaviour (on my computer).
Let's start by loading the libraries and setting up a data.frame
with the grouping id
and spatial coordinate x
.
library(nlme)
nid <- 300
nx <- 10
data <- expand.grid(
x = seq(nx),
id = seq(nid)
)
Now, let's add correlated error and uncorrelated error as separate columns, as well as a random intercept value per id
. The output of arima.sim
requires a normalisation step.
data$ec <- c(
replicate(
nid,
as.numeric(
arima.sim(
model = list(
order = c(1, 0, 0),
ar = 0.5
),
n = nx
)
)
)
)
data$ec <- data$ec / sd(data$ec)
data$eu <- rnorm(nid * nx)
data$random <- rep(rnorm(nid), each = nx)
Now, we can create 3 dependent variables, for 3 models. The first is a mixed model with uncorrelated (regular) error. The second includes an exponential (AR1) correlation structure. The third combines both. I am adding an intercept of 1, an sd of the random effect of 2 and an sd of the total residual error of 3.
data$y1 <- 1 + 2 * data$random + 3 * data$eu
data$y2 <- 1 + 2 * data$random + 3 * data$ec
data$y3 <- 1 + 2 * data$random + sqrt(8) * data$ec + sqrt(1) * data$eu
All of the following lme
models fit without problem, giving the expected result.
l1 <- lme(
fixed = y1 ~ 1,
random = ~ 1 | id,
data = data,
method = "ML"
)
l2 <- lme(
fixed = y2 ~ 1,
random = ~ 1 | id,
correlation = corExp(
form = ~ x | id
),
data = data,
method = "ML"
)
l3 <- lme(
fixed = y3 ~ 1,
random = ~ 1 | id,
correlation = corExp(
form = ~ x | id,
nugget = TRUE
),
data = data,
method = "ML"
)
As far as I know, the following nlme
code specifies exactly the same models as above. The first runs without issues. But the ones with a correlation structure crash R / RStudio. No warning or error message is provided. Fiddling with the arguments and with nlmeControl
does not help, though I do think nlmeControl
could be the place to search for a solution.
nlme(
model = y1 ~ b0,
fixed = b0 ~ 1,
random = b0 ~ 1,
group = ~ id,
data = data,
start = list(
fixed = fixed.effects(l1),
random = setNames(random.effects(l1), "b0")
),
method = "ML"
)
nlme(
model = y2 ~ b0,
fixed = b0 ~ 1,
random = b0 ~ 1,
group = ~ id,
correlation = corExp(
form = ~ x
),
data = data,
start = list(
fixed = fixed.effects(l2),
random = setNames(random.effects(l2), "b0")
),
method = "ML"
)
nlme(
model = y3 ~ b0,
fixed = b0 ~ 1,
random = b0 ~ 1,
group = ~ id,
correlation = corExp(
form = ~ x,
nugget = TRUE
),
data = data,
start = list(
fixed = fixed.effects(l3),
random = setNames(random.effects(l3), "b0")
),
method = "ML"
)
Has anyone experienced this before? Does my example code give the same problem on your computer? What are good strategies to change nlmeControl
to attempt to remedy this?