sim_data_N: Simulate biased (via over-dispersion in N) point count and...
In philipshirk/nmmsims: Simulate & Analyze N-mixture Model Data

Description Usage Arguments Value Examples

Generate point counts and/or distance sampling data that is biased by over-dispersion in the true abundance, N. Distance sampling data is created with each dataset, but it can just be ignored if you only want the point count data. This is a rudementary function. Currently it assumes constant density, detection probability, transects length, etc.

sim_data_N(
  n_sites = 50,
  n_samps = 6,
  lambda1 = 5,
  lambda2 = 5,
  det_prob = 0.42,
  sigma = NA,
  W = 20
)

`n_sites`	number of sites (transects)
`n_samps`	number of samples (replicates) per site
`lambda1`	partial mean abundance at every site (single draw per site that stays constant across samples)
`lambda2`	partial mean abundance at every replicate (new draw for every sample at every site)
`det_prob`	mean detection probability
`sigma`	detection parameter (meters). Just leave this blank and it will be calculated from det_prob
`W`	transect half-width (meters)

Returns a list of 4 items: 1. "true_N" is a matrix of true abundance values for each site (row) and sample (column). 2. "n_obs" is a matrix of the number of observed organisms at each site (row) and sample (column). 3. "y_list" is a list of vectors. Each vector holds the distance data for a single survey. 4. "inputs" is a list of input values.