Roman emperor reign distribution. Examining the claim that there is a bimodal distribution. Data sources: https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-08-13 https://en.wikipedia.org/wiki/List_of_Roman_emperors

This document compiles R resources that I recommend for learning R for spatial data analysis.

For each cost surface (top 3 models), there is a point for each ram location >8Km from core homerange. For each of these points, its cost is compared against 100 pseudopoints along an equidistant boundary to generate a percentile rank. For a purely distance-based cost surface, the actual point will have the same cost as its pseudopoints. Due to noise in the model, there are slight differences so for the Constant1 cost function, it just means average percentile rank is 50 and there is no distance-based trend. The 3 top models all perform very similarly, but typically the log based model has the best (lowest) percentile rank.

individual observations by date.

Average recovery unit snow depths for all snow courses and sensors within 10KM of sheep herd units.Only stations above 8000'. Measurements are by snow year, grouped by the closest recovery unit boundary. Depth in inches.

Brief tutorial on how to process the Campbell Scientific .dat files that come off of our weather stations.

Plots for annual report on # of marks in Sierra Bighorn herds.

Long term snow depth at low-elevation wheeler weather station

Wind summary 2010

hourly battery voltage

Winter points coded by Water Year.

A summary of data reduction techniques for avalanche hazard data, to be used with sheep survival analysis.

Unfinished