Method for Profiling vglm Objects
Investigates the profile log-likelihood function for a fitted model of
class "vglm".
profilevglm(object, which = 1:p.vlm, alpha = 0.01,
maxsteps = 10, del = zmax/5, trace = NULL, ...)object |
the original fitted model object. |
which |
the original model parameters which should be profiled. This can be a numeric or character vector. By default, all parameters are profiled. |
alpha |
highest significance level allowed for the profiling. |
maxsteps |
maximum number of points to be used for profiling each parameter. |
del |
suggested change on the scale of the profile t-statistics. Default value chosen to allow profiling at about 10 parameter values. |
trace |
logical: should the progress of profiling be reported?
The default is to use the |
... |
further arguments passed to or from other methods. |
This function is called by
confintvglm to do the profiling.
See also profile.glm for details.
A list of classes "profile.glm" and "profile" with an
element for each parameter being profiled.
The elements are data-frames with two variables
par.vals |
a matrix of parameter values for each fitted model. |
tau |
the profile t-statistics. |
T. W. Yee adapted this function from
profile.glm,
written originally by D. M. Bates and W. N. Venables.
(For S in 1996.)
The help file was also used as a template.
pneumo <- transform(pneumo, let = log(exposure.time))
fit1 <- vglm(cbind(normal, mild, severe) ~ let, propodds,
trace = TRUE, data = pneumo)
pfit1 <- profile(fit1, trace = FALSE)
confint(fit1, method = "profile", trace = FALSE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.