if( !require('nlme')){
    install.packages('nlme', dependencies=TRUE, repos='http://cran.rstudio.com/')
}
library(nlme)

source('../../BookCode/nlrwr/R/SSexp.R')

load(file='../../BookCode/nlrwr/data/RGRcurve.rda')

# Plot the data to get an idea of what it looks like:
#
plot(RGRcurve$Day, RGRcurve$RGR, xlab='Day', ylab='RGR')
grid()

RGRcurve.m2 = gnls(RGR ~ SSexp(Day, a, b), data=RGRcurve, weights=varExp()) # change the assumed form for the variance
print(summary(RGRcurve.m2))

# Plot the curve and the fit:
#
DayVals = with(RGRcurve, seq(min(Day), max(Day), length.out=100))
RGR_predicted = predict(RGRcurve.m2, newdata=data.frame(Day=DayVals))

plot(RGRcurve$Day, RGRcurve$RGR, xlab='Day', ylab='RGR')
lines(DayVals, RGR_predicted, col='blue')
grid()