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doomlab.github.io | ||
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aosmith.rbind.io
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| | | | | When working with counts, having many zeros does not necessarily indicate zero inflation. I demonstrate this by simulating data from the negative binomial and generalized Poisson distributions. I then show one way to check if the data has excess zeros compared to the number of zeros expected based on the model. | |
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indrajeetpatil.github.io
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zevross.com
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| | | | | We use the R library mgcv for modeling environmental data with generalized additive models (GAMs). It's a great library loaded with functionality but we often find that the default diagnostic ... | |
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www.rdatagen.net
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| | | Inspired by a free online course titled Complier Average Causal Effects (CACE) Analysis and taught by Booil Jo and Elizabeth Stuart (through Johns Hopkins University), I've decided to explore the topic a little bit. My goal here isn't to explain CACE analysis in extensive detail (you should definitely go take the course for that), but to describe the problem generally and then (of course) simulate some data. A plot of the simulated data gives a sense of what we are estimating and assuming. | ||
