assessMh: This function asseses some frequentist properties when...
In benaug/Mbmisscap: Mbmisscap

This function asseses some frequentist properties when naively fitting Mb to capture histories that are missing data.

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assessMh(N, p, occ, K, traptype, lambda_h, lambda_c = NULL, delta = NULL,
  kappa_h = NULL, kappa_t = NULL, cluster = FALSE, kappa_c = NULL,
  alpha = NULL, hettype = "logitnormal", sims = 100, cores = 1)

`N`	an integer that is the true population size
`p`	a vector of size 2 containing the capture and recapture probabilities
`occ`	an integer that is the number of capture occasions to simulate
`K`	an integer that is the number of traps to simulate
`traptype`	a character string specifying the trap type. "single" allows individuals to be caught in at most 1 trap per occasion and "multi" allows individuals to be caught in multiple traps per occasion.
`lambda_h`	a positive value specifying the parameter for the zero-truncated Poisson hair deposition process (S_ijk\|W_ijk=1)
`lambda_c`	a positive value specifying the parameter for the zero-truncated Poisson cluster deposition process if cluster=TRUE
`delta`	a numeric value between 0 and 1 specifying the probability a hair sample will be retained in the subsample. This is used if subsampling is done by pooling samples on each occasion and taking a simple random sample.
`kappa_h`	an integer specifying the number of hair samples to retain per occasion-trap if cluster=FALSE or per occasion-trap-cluster if cluster=TRUE. Used in sub-hair and sub-cluster methods
`kappa_t`	an integer specifying the number of traps per occasion at which to retain kappa_h hair samples. If no value is specified no trap-level subsampling occurs. Only works when cluster=FALSE. Used in the sub-trap method
`cluster`	a logical indicating whether or not to simulate from the cluster model (multiple clusters per individual-occasion-trap)
`kappa_c`	an integer specifying the number of clusters per trap-occasion at which to retain kappa_h hair samples. Only works when cluster=TRUE. Sub-cluster method.
`alpha`	a numeric value between 0 and 1 specifying the probability that a hair sample produces an individual identification
`hettype`	...
`sims`	the number of simulated data sets to generate and fit Mb to
`cores`	the number of cores to do the simulation on. A typical for loop is used if cores=1 and the foreach package is used if cores>1