CreateHomeRangeKernelsPareto: Create home range kernels using a Pareto distribution
In Blakemassey/baear: Functions for Bald Eagle Data Manipulation and Model Fitting

Creates RasterLayers of homerange kernels based on home centroids

1 2	CreateHomeRangeKernelsParetoGamma(df_all, df_home, base, max_r, home_shape, home_scale, min_prob, id, name, output_dir, write_homerange)

`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
`home_shape`	inflection point of the Logistic function that governs the home kernel
`home_scale`	scale parameter of the Logistic function that governs the scale parameter
`id`	column name of df_home that identifies the homerange. Default is NULL, which sets the names to df_home row number.
`name`	column name of df_home that identifies the name of the homerange and is used to write the name of the .tif file. Default is 'id', which sets the names to df_home row number if'id' is NULL.
`min_prob`	numeric, minimum probablity threshold; all probabilities below this value will be rounded to zero. Default is 0.
`output_dir`	directory for output files (distance, homerange)
`write_homerange`	logical, write home range raster to file. Default is FALSE