Statistical Programming
The University of Edinburgh (ED)
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Summary
Statistical Programming in R: Complete Revision Guide with Tested Code and Worked Output
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The University of Edinburgh
Statistical Programming
A 20-page revision guide to statistical programming in R. It covers git and GitHub, vectors, data frames and functions, the apply family and pipes, simulation and coverage studies, regex and tidy data, linear models and design matrices, S3 classes, Cholesky/QR/SVD and conditioning, debugging, testing and profiling, maximum likelihood with optim and Newton's method, base and ggplot2 graphics, the bootstrap, Metropolis-Hastings, Gibbs sampling, JAGS and R Markdown. Every code example was run an...
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