https://github.com/cran/bbmle
Tip revision: 2fdcf71f4804d26c8df6ee5191e94caa3c1ae9b7 authored by Ben Bolker on 10 January 2011, 19:45:12 UTC
version 0.9.7
version 0.9.7
Tip revision: 2fdcf71
predict.Rout.save
R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> library(bbmle)
Loading required package: stats4
Loading required package: numDeriv
Loading required package: lattice
> set.seed(1002)
> lymax <- c(0,2)
> lhalf <- 0
> x <- runif(200)
> g <- factor(rep(c("a","b"),each=100))
> y <- rnbinom(200,mu=exp(lymax[g])/(1+x/exp(lhalf)),size=2)
> d <- data.frame(x,g,y)
>
> fit3 <- mle2(y~dnbinom(mu=exp(lymax)/(1+x/exp(lhalf)),size=exp(logk)),
+ parameters=list(lymax~g),
+ start=list(lymax=0,lhalf=0,logk=0),data=d)
>
> plot(y~x,col=g)
> ## true curves
> curve(exp(0)/(1+x/exp(0)),add=TRUE)
> curve(exp(2)/(1+x/exp(0)),col=2,add=TRUE)
> xvec = seq(0,1,length=100)
> lines(xvec,predict(fit3,newdata=list(g=factor(rep("a",100),levels=c("a","b")),
+ x = xvec)),col=1,lty=2)
> lines(xvec,predict(fit3,newdata=list(g=factor(rep("b",100),levels=c("a","b")),
+ x = xvec)),col=2,lty=2)
>
> p1 = predict(fit3)
> ## manual prediction
> p2A =
+ with(as.list(coef(fit3)),exp(`lymax.(Intercept)`)/(1+x[1:100]/exp(lhalf)))
> p2B = with(as.list(coef(fit3)),exp(`lymax.(Intercept)`+lymax.gb)/(1+x[101:200]/exp(lhalf)))
> p2 = c(p2A,p2B)
> all(p1==p2)
[1] TRUE
>
>
>
> proc.time()
user system elapsed
0.972 0.164 1.080