CreateHomeRangeKernelsParetoGamma: Create home range kernels based on Pareto and Gamma functions

In Blakemassey/baear: Functions for Bald Eagle Data Manipulation and Model Fitting

Description

Creates RasterLayers of homerange kernels based on home centroids

Usage

CreateHomeRangeKernelsParetoGamma(
  df_all,
  df_home = df_all,
  base = base,
  max_r,
  pareto_shape,
  pareto_scale,
  gamma_shape,
  gamma_scale,
  id = "nest_id",
  output_dir = getwd(),
  write_distance = TRUE,
  write_homerange = TRUE
)

Arguments

df_all	dataframe of all homerange centroids
df_home	dataframe of homerange centroids to calculate homerange kernels (these must be a subset of the df_all dataframe), Default is to use 'df_all' dataframe
base	base Raster that sets the projection, extent, and dimensions of the study area
max_r	maximum radius to calculate the homerange raster from each df_home centroid
pareto_shape	shape parameter of the Logistic function that governs the home kernel
pareto_scale	scale parameter of the Logistic function that governs the home kernel
gamma_shape	shape parameter of the Gamma function that governs the conspecific avoidance kernel
gamma_scale	scale parameter of the Gamma function that governs the conspecific avoidance kernel
id	column name of df_home that identifies the homerange. Default is NULL, which sets the names to df_home row number.
output_dir	directory for output files (distance, homerange)
write_distance	logical, write distance raster to file. Default is FALSE.
write_homerange	logical, write home range raster to file. Default is FALSE

Value

A list containing homerange kernel Rasters for all the df_home centroids

Blakemassey/baear documentation built on Dec. 25, 2021, 9:48 a.m.