rqResObs_optim: Observation Randomized Quantile Residuals

In philipshirk/nmmsims: Simulate & Analyze N-mixture Model Data

Description

Calculates Observation Randomized-quantile residuals for a model fit with optim. As defined in Knape et al. 2018 and available for unmarked models in the nmixgof package.

Usage

rqResObs_optim(
  n_obs,
  K,
  lambda_est,
  sigma_est = NA,
  W = NA,
  p_est = NA,
  y_list = NA,
  sampling_method,
  show.warnings = FALSE
)

Arguments

n_obs	a matrix of observed counts, with rows = sites and columns = replicates
K	maximum possible true mean abundance, N
lambda_est	estimated lambda (mean abundance across sites) from fitted model
sigma_est	estimated sigma from fitted model (only needed if distance sampling)
W	transect half-width. (only needed if distance sampling)
p_est	estimated mean (across distances = 0 to W) detection probability (only needed if point counts)
y_list	list of distance values with elements = sites and replicates elements within each element
sampling_method	either 'pointcount' or 'distance'

Value

a matrix of residuals with the same dimensions as the observations, n_obs.

philipshirk/nmmsims documentation built on Feb. 26, 2020, 11:27 a.m.