Hi, I am trying to adjust my empirical data to the nonlinear models, I have tried to use the initial values for each model of close species and averages as indicated in the package guides. I have also used my data as vectors and as data frames. However, in all cases I have obtained the errors below:

bri1_egg <- devRateModel(
eq = briere1_99,
temp = temp,
devRate = devRate,
startValues = list(aa = 1.12, Tmin = 0.021, Tmax = 32.29))
Error in numericDeriv(form[[3L]], names(ind), env, central = nDcentral) :
Missing value or an infinity produced when evaluating the model

bri1_egg <- devRateModel(
eq = briere1_99,
dfData = larvae,
startValues = list(aa = 0.85, Tmin = 9, Tmax = 37))
Error in stats::nls(formula = eq[[1]], data = data.frame(rT = devRate, :
parameters without starting value in 'data': rT

lactin1_95 <- devRateModel(
eq = lactin2_95,
temp = temp,
devRate = devRate,
startValues = list(
aa = 0.03, Tmax = 30, deltaT = 5.0, bb = -1.5))
Error in stats::nls(formula = eq[[1]], data = data.frame(rT = devRate, :
singular gradient

taylor_egg <- devRateModel(eq = taylor_81,
temp = temp,
devRate = devRate,
startValues = list(Rm = 0.05, Tm = 30, To = 5))
Error in stats::nls(formula = eq[[1]], data = data.frame(rT = devRate, :
singular gradient

I would appreciate if you could guide me in possible solutions