library(nlme)
data(Soybean)
xyplot(weight ~ Time, data = Soybean, subset = Plot == "1988F2")
Soybean.1 <- Soybean[Soybean$Plot == "1988F1",]
fit.nls <- nls(weight ~ Asym/(1 + exp((xmid - Time)/scal)), 
               data = Soybean.1,
               start = c(Asym = 20, xmid = 60, scal = 10))

newdat <- data.frame(Time = seq(10, 90))
preds <- predict(fit.nls, newdata = newdat)

xyplot(preds ~ Time, data = newdat, type='l',
       ylab = 'Weight',
       panel = function(x,y,...){
         panel.xyplot(x,y,...)
         panel.xyplot(Soybean.1$Time, Soybean.1$weight, type = 'p')
       }) 

fit.nls2 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal) , data = Soybean.1)

## Example of logistic function

logis <- function(x, Asym , xmid, scal){

  y <- Asym/(1 + exp((xmid - x)/scal))
  y

}

x <- seq(0,35)

y <- logis(x, 30, 15, 2)


xyplot(y ~ x, type = 'l')

pdf('../figs/logis.pdf')
xyplot(y ~ x, type = 'l')
dev.off()