This repo has the code for Easton's course project in STATS 608: Monte Carlo Methods in Statistics. It fits a discrete Log-normal normal to count data, estimating the mean and variance as functions of a design matrix, x. Optionally, it can also estimate an autocorrelation parameter. Feel free to reuse this code and the ideas contained in it. If you'd like to write a scientific paper based on this model, I would love to be involved. You can contact me on LinkedIn (linkedin.com/in/eastonhuch/).
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