r - Confidence Interval for mle2 Regression Line -


i doing non-linear regression mle2 in r , want generate 95% point-wise confidence band around curve of best fit. simplified example of trying shown below, try use predict on mle2 fit object. suggestions on how this?

library(bbmle)  # fabricated data e.u <- function( x, k ) { exp(-k * x) } n <- 40 t.bio <- 1:n bio <- 10*e.u(t.bio,log(2)/10) + rnorm(n,0,sqrt(e.u(t.bio,log(2)/10)))  #use mle2 estimate parameters intake.guess <- 10 rc.guess <- 0.07  n.log.like <- function(intake,k) {   sum.y <- 0   (i in 1:length(bio)) {     x <- intake * e.u(t.bio[i],k)     y <- bio[i]     sum.y <- sum.y + log( dnorm(y,x,0.1*sqrt(y)) ) }   return(-sum.y) }     b <- mle2(n.log.like,         start=list(             intake=intake.guess,             k=rc.guess),         data=list(             t.bio=t.bio,             bio=bio),         method="nelder-mead",         skip.hessian=false)  intake <- coef(summary(b))[1,1]          rc <- coef(summary(b))[2,1]          summary(b)  #scatter plot bio.p <- numeric(n) x <- 1:n (i in 1:n) { bio.p[i] <- intake * e.u(x[i],rc) } plot(x,bio.p,type="l",log="xy",main="",      xlab="days after intake",ylab="excretion") points(t.bio,bio)  #i want generate confidence interval on regression line bio.hat <- predict(b)

you may want try resource:

https://stat.ethz.ch/r-manual/r-patched/library/stats/html/predict.lm.html

there se.fit parameter passed predict(). if true, calculate se. have not tried it.

another way use library(ggplot2), 1 of parameters can confidence level overlayed on plot automatically. example, 

c <- ggplot(mtcars, aes(qsec, wt)) c + stat_smooth(se = true) + geom_point()

this put band around plot indicate confidence interval. se set true default.

reference: http://svitsrv25.epfl.ch/r-doc/library/ggplot2/html/stat_smooth.html

third, may calculate confidence interval , overlay plot setting par(new=true). may cumbersome still feasible.


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