findDistThresh: Identify Point-Based Distance Threshold for Contact
In contact: Creating Contact and Social Networks

Description Usage Arguments Details Value References Examples

Sample from a multivariate normal distribution to create "in-contact" n point pairs based on real-time-location systems accuracy, and generate a distribution describing observed distances between point pairs.

findDistThresh(
  n = 1000,
  acc.Dist1 = 0.5,
  acc.Dist2 = NULL,
  pWithin1 = 90,
  pWithin2 = NULL,
  spTh = 0.666
)

`n`	Integer. Number of "in-contact" point-pairs used in the expected-distance distribution(s). Defaults to 1000.
`acc.Dist1`	Numerical. Accuracy distance for point 1.
`acc.Dist2`	Numerical. Accuracy distance for point 2. If == NULL, defaults to acc.Dist1 value.
`pWithin1`	Numerical. Percentage of data points within acc.Dist of true locations for point 1.
`pWithin2`	Numerical. Percentage of data points within acc.Dist of true locations for point 2. If == NULL, defaults to pWithin1 value.
`spTh`	Numerical. Pre-determined distance representing biological threshold for contact.

This function is for adjusting contact-distance thresholds (spTh) to account for positional accuracy of real-time-location systems, assuming random (non-biased) error in location-fix positions relative to true locations. Essentially this function can be used to determine an adjusted spTh value that likely includes the majority of true contacts defined using the initial spTh.

Output is a list containing 5 named vectors. The first vector describes summary statistics of the simulated distance distribution. The second and third vectors describes varied confidence intervals (50-99 for the simulated distribiution. The fourth vector describes adjusted spTh values that will capture approximately 84, 98, and 100 contacts given the pre-determined spTh value (all calculated using the Empirical rule). Finally, the fifth vector describes the actial observed frequency of captured true contact given the spTh adjustments listed in the fourth vector.

Farthing, T.S., Dawson, D.E., Sanderson, M.W., and Lanzas, C. 2020. Accounting for space and uncertainty in real-time-location- system-derived contact networks. Ecology and Evolution 10(11):4702-4715.