nmmsims: Simulate & Analyze N-mixture Model Data

Description Usage Arguments Value Examples

This takes a single dataset of point count and/or distance sampling data and analyses it in 1 to 4 ways.

analyse_data(
  simulated_data,
  reps_to_analyze = c(3, 6),
  sampling_method = c("distance", "pointcount"),
  analysis_method = c("optim", "unmarked"),
  simulate_gof_pvals = FALSE,
  simulate_gof_sims = 5,
  simulate_gof_parallel = FALSE,
  W = 20,
  return = "results"
)

`simulated_data`	the output from one of the sim_data functions in this package
`reps_to_analyze`	the number of samples/replicates to analyze. If NA, it will analyse all replicates in the data.
`sampling_method`	Analyze as distance sampling or point count. Options = 'distance' and/or 'pointcount'
`analysis_method`	Analyze using optim or package unmarked. Options = 'optim' and/or 'unmarked'
`simulate_gof_pvals`	Logical. Whether or not to simulate goodness-of-fit p-values, which is a VERY time-consuming process. Defaults to FALSE.
`simulate_gof_sims`	Number of simulations to use for simulating goodness-of-fit p-values. Only used if simulate_gof_pvals = TRUE
`simulate_gof_parallel`	Logical. Whether or not to use parallel processing to simulate goodness-of-fit p-values. Only used if simulate_gof_pvals = TRUE. Defaults to FALSE
`W`	transect half-width (in meters)
`return`	What to return from the function call. Currently the only option is 'results'. May change this to only analyze simulated goodness-of-fit metrics.