twinSIR_profile: Profile Likelihood Computation and Confidence Intervals

In jimhester/surveillance: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Description

Function to compute estimated and profile likelihood based confidence intervals. Computations might be cumbersome!

Usage

## S3 method for class 'twinSIR'
profile(fitted, profile, alpha = 0.05,
        control = list(fnscale = -1, factr = 10, maxit = 100), ...)

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.
...	unused (argument of the generic).

Value

list with profile log-likelihood evaluations on the grid and highest likelihood and wald confidence intervals. The argument profile is also returned.

Author(s)

Michael Höhle and Sebastian Meyer

Examples

if (surveillance.options("allExamples")) {
  data("foofit")
  prof <- profile(foofit, list(c(1,NA,NA,5), c(3,NA,NA,0), c(4, 0.5, 1.1, 10)))
  prof

  ## there is also a plot-method for "profile.twinSIR"
  plot(prof)
}

jimhester/surveillance documentation built on May 19, 2019, 10:33 a.m.