
Last chance! 50% off unlimited learning
Sale ends in
Compute the profile likelihood of a finite mixture model for a user-specified range of values for the mixing parameter. This provides a check on multimodality.
pmixProfileLL(CH, model = list(g0 ~ h2, sigma ~ h2), CL = TRUE, pmvals = seq(0.01,
0.99, 0.01), pmi = 5, ncores = 1, ...)
secr.fit
secr.fit
secr.fit
Numeric vector of profile likelihoods.
See secr-finitemixtures.pdf.
Choosing the wrong value for pmi results in the error message "invalid fixed beta - require NP-vector". The easiest way to find the value of pmi
is to inspect the
output from a previously fitted mixture model - either count the coefficients
or check fit$parindx$pmix (for a model named `fit'). It is assumed that `pmix' is the last real
parameter in the model, and that pmix is constant.
## Not run: ------------------------------------
#
# pmvals <- seq(0.02,0.99,0.02)
# mask <- make.mask(traps(ovenCH[[1]]), nx = 32, buffer = 100)
# ## only g0 ~ h2, so reduce pmi
# outPL <- pmixProfileLL(ovenCH[[1]], model = list(g0~h2), mask
# = mask, pmvals, CL = TRUE, ncores = 5, pmi = 4) ## slow!
# plot(pmvals, outPL, xlim = c(0,1),
# xlab = 'Fixed pmix', ylab = 'Profile log-likelihood')
#
## ---------------------------------------------
Run the code above in your browser using DataLab