This function calculates loglikelihood profiles for the selected variables. Despite the function name, these are not true profile likelihoods as they hold all other coefficients fixed at their MLE.
1 2 3 4 
obj 
object of 
method 
estimation method to use 
vars 
numeric vector selecting a set of covariates from the fitted model 
k 
integer indicating the number of points at which the loglikelihood should be calculated. 
as.table 
logical (default 
scales 
list of settings for the scales argument passed to

between 
numeric specifying the space between panels. 
main 
string, plot title 
xlab 
string, the 
ylab 
string, the 
... 
Additional arguments to pass to 
Returns an object of boolprofclass
, the default
action being to present the default plot.
Jason W. Morgan (morgan.746@osu.edu)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ## Not run:
## Note: This example assumes a boolean model has already been fit.
## Display the contours of the likelihood given a change the value of
## the coefficients.
(prof < boolprof(fit))
## Extract the plots for x1_a and x4_b.
plot(prof, y = c("x1_a", "x4_b"))
plot(prof, y = c(1, 3), scales = list(y = list(relation = "free")))
## You can also use variable or index matching with boolprof to select
## particular covariates of interest.
boolprof(fit, vars = c(1, 3))
boolprof(fit, vars = c("x1_a", "x4_b"))
## End(Not run)

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