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()

# Guess at some initial values:
#
y0 = min(RGRcurve$RGR)

x = 4 # a point on the curve
y = 0.5
b = x/log(y / y0)

fit = nls(RGR ~ y0*exp(Day/b), data=RGRcurve, start=c(y0=y0, b=b), trace=TRUE)
print(summary(fit))

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

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