Dear R users,

I am struggling to fit expo-linear equation to my data using "nls" function. I am always getting error message as i highlighted below in yellow color: 


 Theexpo-linear equation which i am interested to fit my data:   
    response_variable =  (c/r)*log(1+exp(r*(Day-tt))), where "Day" is time-variable

my response variable

rl <- c(2,1.5,1.8,2,2,2.5,2.6,1.5,2.4,1.7,2.3,2.4,2.2,2.6,
                 2.8,2,2.5,1.8,2.4,2.4,2.3,2.6,3,2,2.6,1.8,2.5,2.5,
                 2.3,2.7,3,2.2,2.6,1.8,2.5,2.5,2.3,2.7,3,2.2)
myday <- rep(c(3,5,7,9,10), each = 8) # creating my predictor time-variable
mydata <- data.frame(rl,myday) # data object

# fitting model equation in "nls" function, when i assigned initial value for tt = 0.6,

CASE-I: 

> mytest <- nls(rl ~ (c/r)*log(1+exp(r*(myday-tt))), data = mydata,
+ na.action = na.omit, 
+ start = list(c = 2.0, r = 0.05, tt = 0.6),algorithm = "plinear")
Error in numericDeriv(form[[3L]], names(ind), env) : 
  Missing value or an infinity produced when evaluating the model
 
CASE - II:
When i assigned initial value for tt = 1: 
 
> mytest <- nls(rl ~ (c/r)*log(1+exp(r*(myday-tt))), data = mydata,
+ na.action = na.omit, 
+ start = list(c = 2.0, r = 0.5, tt = 1),algorithm = "plinear")
Error in nls(rl ~ (c/r) * log(1 + exp(r * (myday - tt))), data = mydata,  : 
  singular gradient
 
I am getting the yellow-color highlighted error message (see above). Truely speaking, i have not so much experienced with fitting specific model equation in R-package.
I have following queries: 
 
1. Does any one can explain me what is going wrong here ? 
 
2. Importantly, how can i write above equation into "nls" functions ? 
 
I will be very thankful to you, if any one can help me.
I am looking for your cooperations.

Thanks


Regards,
Ram Kumar Basnet
	[[alternative HTML version deleted]]

