# How to provide fixed values for some random parameters in nlme in R?

I'd like to fit a mixed-effects logistic growth curve to grouped data using the nlme package in R. The function has the following form:

$$y_t = \dfrac{Ay_0}{y_0+(A-y_0)e^{-rt}}$$

where the parameters $$A$$ (asymptote), $$r$$ (rate) and $$y_0$$ (initial value) are allowed to vary by group. Such a model can be fitted with nlme as follows:

grpdat <- groupedData(y ~ time | group, data=mydata)

logist <- deriv( ~A*y0/(y0+(A-y0)*exp(-r*t)),
c("A", "r", "y0"),
function(t, A, r, y0){} )

# without random effects:
mod0 <- nlsList(model = y ~ logist(time, A, r, y0),
data = grpdat,
start = list(A = 100, r = 1, y0 = 0.1))

# with random effects:
mod1 <- nlme(mod0, random = list(A ~ 1, r ~ 1, y0 ~ 1))


My question: I have actually observed the values of $$y_0$$ for each group. How can I specify these, rather than estimate them?