fit.occ.4method: Fit occupancy model with four detection methods

In dsouthwell/TestPackagev2: Spatially explicit power analysis in dynamic landscapes

Description

This function fits an occupancy model to simulated detection histories using the package unmarked for species that are detected using 4 detection methods A trend in occupancy is estimated and confidence intervals are calculated depending on the Type I error rate. A one-tailed or two-tailed significance test is then conducted on the trend parameter A one-tailed test looks to see if the upper or lower confidence interval is greater than or less than zero. A two-tailed test assesses whether both the upper and lower confidence intervals have the same sign (i.e. are both positive or negative). If park.power = TRUE, model fitting is repeated on sites from each regional level management unit.

Usage

fit.occ.4method(method1, method2, method3, method4, repeats1, repeats2,
  repeats3, repeats4, s.years, n.sites, xy.sites, park.ID, park.level, powcnt,
  fail, pow.park, fail.park, value, ss, two.tailed, n.park)

Arguments

method1	The first detection method relevant to species ss
method2	The second detection method relevant to species ss
method3	The third detection method relevant to species ss
method4	The fourth detection method relevant to species ss
repeats1	The number of repeat visits for the first detection method
repeats2	The number of repeat visits for the second detection method
repeats3	The number of repeat visits for the third detection method
repeats4	The number of repeat visits for the fourth detection method
s.years	A vector specifying the years that monitoring occurs. Note, monitoring must be done in the final year (i.e. Tmax)
n.sites	The number of sites monitored
xy.sites	The XY coordinates of monitored sites
park.ID	A vector specifying that location of each site with sub-level parks
park.level	Set to TRUE is power is estimated within regional level management unit, FALSE otherwise
powcnt	A vector that keeps track of how many times a significant trend in occupancy is detected across the landscape
fail	A vector that keeps track of how many times the occupancy model could not be fitted to simulated detection histories at a landscape level in unmarked
pow.park	A vector that keeps track of how many times a significant trend in occupancy is detected within each park
fail.park	A vector that keeps track of how many times the occupancy model could not be fitted to simulated detection histories at a park level in unmarked
value	The critical value used to calculate confidence intervals around the trend parameter, depending on the Type I error rate and a one-tailed or two-tailed test
ss	An index to loop through each species
two.tailed	Set to TRUE if conducting a two-tailed test, FALSE otherwise
n.park	The number of parks in which to estimate power

dsouthwell/TestPackagev2 documentation built on May 28, 2019, 9:38 a.m.