gdist.prep: Prepare data for optimization using 'gdistance'

In wpeterman/ResistanceGA: Optimize resistance surfaces using genetic algorithms

Prepare data for optimization using gdistance

Description

Creates a necessary input for optimizing resistance surfaces based on pairwise cost distances, implemented using the gdistance library

Usage

gdist.prep(n.Pops, 
                  response = NULL,
                  samples,
                  covariates = NULL,
                  formula = NULL,
                  transitionFunction = function(x)  1 / mean(x),
                  directions = 8,
                  longlat = FALSE,
                  method = 'commuteDistance',
                  min.max_dist = NULL,
                  keep = NULL)

Arguments

n.Pops	The number of populations that are being assessed
response	Vector of pairwise genetic distances (lower half of pairwise matrix).
samples	Either provide the path to a .txt file containing the xy coordinates, or provide a matrix with x values in column 1 and y values in column 2. Alternatively, you can provide a SpatialPoints object
covariates	Data frame of additional covariates that you want included in the MLPE model during opitmization.
formula	If covariates are included in the model, specify the R formula for the fixed effects portion of the MLPE model.
transitionFunction	The function to calculate the gdistance TransitionLayer object. See transition. Default = function(x) 1/mean(x)
directions	Directions in which cells are connected (4, 8, 16, or other). Default = 8
longlat	Logical. If true, a geoCorrection will be applied to the transition matrix. Default = FALSE
method	Specify whether pairwise distance should be calulated using the costDistance or commuteDistance (Default) functions. costDistance calculates least cost path distance, commuteDistance is equivalent (i.e. nearly perfectly correlated with) resistance distance calculated by CIRCUITSCAPE.
min.max_dist	NOT YET SUPPORTED. Optional. Specify the minimum and maximum distance at which pairwise comparisons will be made(e.g., c(1, 50)). Euclidean distances below and above the minumum and maximum values will be omitted from the analysis. This has potential to reduce analysis time, but also reduces the number of pairwise comparisons.
keep	NOT YET SUPPORTED. An optional vector equal to length response (i.e. all pairwise observations), with 1 indicating to keep the observation, and 0 to drop the observation. This can be used in conjunction with, or in place of min.max_dist to select which observations to include in analyses.

Details

When specifying a formula, provide it as: response ~ covariate. the formula response will use the vector of values specified for the response parameter. Make sure that covariate names match variable names provided in covariates

Value

An R object that is a required input into optimization functions

Author(s)

Bill Peterman <[e-mail]>

Examples

 
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wpeterman/ResistanceGA documentation built on Nov. 20, 2023, 11:50 p.m.