Parker, M.R.P., Pattison, V. & Cowen, L.L.E. (2020). Estimating population abundance using counts from an auxiliary population. Environmental Ecological Statistics 27, 509–526.
Bootstrapping is a statistical technique for analyzing the distributional properties of sample data (such as variability and bias). It has many uses, and is generally quite easy to implement. Continue reading to learn how you can perform a bootstrap procedure in R!
What is bootstrapping? The bootstrap essentially uses re-sampling of a set of sample data in order to observe properties of the distribution of the data. For each re-sampling of the data (each “bootstrap sample”), you sample with replacement from the sample data, and compute the statistic of interest on the bootstrap sample (the bootstrap statistic).
Parker, M. R. P. (2020). N-mixture models with auxiliary populations and for large population abundances [Thesis].