https://github.com/cran/bbmle
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Tip revision: 1fe1daaec4e0e4abab833a89e3d7729279ad0c18 authored by Ben Bolker on 16 January 2012, 00:00:00 UTC
version 1.0.4.1
Tip revision: 1fe1daa
predict.Rout.save

R Under development (unstable) (2012-01-01 r58032)
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> library(bbmle)
Loading required package: stats4
Loading required package: numDeriv
Loading required package: lattice
Loading required package: MASS
> 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 
  0.928   0.924   1.725 
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