Jolly-Seber model: fits model, formats inference, and simulates from fitted model.
form: a named list of formulae for each parameter (~1 for constant)
scr_data: a ScrData object
start: a named list of starting values
num_cores (optional, default = 1): number of processors cores to use in parallelised code
print (defualt = TRUE): if TRUE then helpful output is printed to the screen
Methods include:
get_par(name, j, k, m): returns value of parameter "name" for detector j on occasion k (if j, k omitted then returns value(s) for all)
set_par(par): can change the parameter the model uses. Note, the model will simulate data using this parameter, but will only present inference based on the maximum likelihood estimates.
set_mle(mle, V, llk): set maximum likleihood for this model with parameters mle, covariance matrix V, and maximum likelihood value llk
calc_D_llk(): computes the likelihood of the D parameter
calc_initial_distribution(): computes initial distribution over life states (unborn, alive, dead)
calc_pr_entry(): computes vector with entry j equal to probability of individual unborn up to occasion j being born just after occasion j
calc_tpms(): returns list of transition probability matrix for each occasion
calc_pr_capture(): returns array where (i,k,m) is probability of capture record on occasion k for individual i given activity centre at mesh point m
calc_pdet(): compute probability of being detected at least once during the survey
calc_llk(): compute log-likelihood at current parameter values
fit(): fit the model by obtaining the maximum likelihood estimates. Estimates of density are obtained from parametric boostrap with nsim resamples.
simulate(): simulate ScrData object from fitted model
par(): return current parameter of the model
mle(): return maximum likelihood estimates for the fitted model
data(): return ScrData that the model is fit to
estimates(): return estimates in a easy to extract list
cov_matrix(): return variance-covariance matrix from fitted model (on working scale)
mle_llk(): return log-likelihood value of maximum likelihood estimates
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An object of class R6ClassGenerator
of length 24.
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