Dear all,
I have a question about lattice use. I would like to use it to represent:
- my raw data as points,
- and the results of a non linear fit as a line,
- having 2 groups data (and so 2 colors).
However, as I have few raw data, I would like to increase the number of
points to smooth the line which correspond to the fit.
So my questions are:
- How can I use the group argument to make new predictions inside panel
argument ?
- How can I use this prediction inside the panel argument to draw the fit
per group?
Hereafter a minimal example:
#==================================================
library(lattice)
set.seed(2)
# Dummy dataframe
foo <- data.frame(
time = seq(0, 60, 5),
char = sample(c("A", "B"), size = 13, replace = TRUE)
);
# Simulated response vector according a Gompertz function + rnorn(0, 5)
foo$y <- SSgompertz(foo$time, Asym = 100, b2 = ifelse(foo$char == 'A', 6,
10),
b3 = ifelse(foo$char == "A", .91, .8)) +
rnorm(nrow(foo), mean=0, sd = 5);
# Non-linear fit on simulation data
res_nls <- nls(
y ~ SSgompertz(time, Asym = 100, b2[char], b3[char]), data = foo,
start = list( b2 = c(7,7), b3 = c(0.9, 0.9)));
# My problem
xyplot(y ~ time, groups = char, data = foo,
panel = function(x, y, groups=groups, model = model, ...){
panel.xyplot(x,y, groups = groups, ...);
newdata <- data.frame(time = x, char = groups);
newdata$y <- predict(model, newdata = newdata);
panel.superpose(x = newdata$time, y=newdata$y, groups = groups, ...,
panel.groups = function(x,y, col, col.symbol, ...){
panel.lines(x,y, col.line = col.symbol)
})
}, model = res_nls);
#==================================================
Many thanks,
Francois
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