twinSIR_profile: Profile Likelihood Computation and Confidence Intervals
Description
Function to compute estimated and profile likelihood based confidence
intervals. Computations might be cumbersome!
There is a simple plot-method for the result.
a list with profile log-likelihood evaluations on the grid and highest likelihood
and Wald confidence intervals. The argument profile is also returned.
The result has class "profile.twinSIR", for which a simple (undocumented)
plot-method is available.
Arguments
fitted
an object of class "twinSIR".
profile
a list with elements being numeric vectors of length 4. These vectors must
have the form c(index, lower, upper, gridsize).
index:
index of the parameter to be profiled in the vector coef(fitted).
lower, upper:
lower/upper limit of the grid on which the profile log-likelihood is
evaluated. Can also be NA in which case lower/upper equals
the lower/upper bound of the respective 0.3 % Wald confidence interval
(+-3*se).
gridsize:
grid size of the equally spaced grid between lower and upper. Can also
be 0 in which case the profile log-likelihood for this parameter is not
evaluated on a grid.
alpha
\((1-\alpha) 100\%\) profile likelihood based confidence
intervals are computed. If alpha <= 0, then no confidence intervals are
computed.
control
control object to use in optim for the profile log-likelihood
computations.
data("hagelloch")
fit <- twinSIR(~ household, data = hagelloch)
gridsize <- if (interactive()) 35else5# for fast testsprof <- profile(fit, list(c(1, NA, NA, gridsize)))
prof$ci.hl
plot(prof)