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www.rdatagen.net
| | kgoldfeld.github.io
3.2 parsecs away

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| | Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
| | aosmith.rbind.io
2.4 parsecs away

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| | I walk through an example of simulating data from a binomial generalized linear mixed model with a logit link and then exploring estimates of over/underdispersion.
| | kgoldfeld.github.io
2.5 parsecs away

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| |
| | yasoob.me
15.3 parsecs away

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| Hey guys! I recently wrote a review paper regarding the use of Machine Learning in Remote Sensing. I thought that some of you might find it interesting and insightful. It is not strictly a Python focused research paper but is interesting nonetheless. Introduction to Machine Learning and its Usage in Remote Sensing 1. Introduction Machines have allowed us to do complex computations in short amounts of time. This has given rise to an entirely different area of research which was not being explored: teachin...