https://github.com/cran/bbmle
Tip revision: a30256c01413bbf7af580b5ae24547064a7d055e authored by Ben Bolker on 18 April 2017, 12:04:25 UTC
version 1.0.19
version 1.0.19
Tip revision: a30256c
testenv.R
library(bbmle)
f <- function() {
maxit <- 1000
d <- data.frame(x=0:10,
y=c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8))
mle2(y~dpois(lambda=exp(lymax)/(1+x/exp(lhalf))),
start=list(lymax=0,lhalf=0),
data=d,
control=list(maxit=maxit),
parameters=list(lymax~1,lhalf~1))
}
f2 <- function(method="BFGS") {
d <- data.frame(x=0:10,
y=c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8))
mle2(y~dpois(lambda=exp(lymax)/(1+x/exp(lhalf))),
start=list(lymax=0,lhalf=0),
data=d,
method=method,
parameters=list(lymax~1,lhalf~1))
}
m1 <- f()
p <- profile(m1)
## FIXME: check results (need to save in an environment-friendly way!)
print(head(as.data.frame(p)),digits=3)
m2 <- f2()
p2 <- profile(m2)
print(head(as.data.frame(p2)),digits=3)