Publications by Joseph Rickert
February 2025 Top 40 New CRAN Packages
In February, one hundred fifty-nine new packages made it to CRAN. Here are my Top 40 picks in fifteen categories: Artificial Intelligence, Computational Methods, Ecology, Genomics, Health Sciences, Mathematics, Machine Learning, Medicine, Music, Pharma, Statistics, Time Series, Utilities, Visualization, and Weather. Artificial Intelligence chores ...
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January 2025 Top 40 New CRAN Packages
In January, one hundred eighty-six new packages made it to CRAN. Here are my Top 40 picks in sixteen categories: Archaeology, Artificial Intelligence, Computational Methods, Ecology, Epidemiology, Finance, Genomics, Health Technology Assessment, Machine Learning, Medicine, Music, Pharma, Statistics, Time Series, Utilities, and Visualization. Archa...
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A First Look at TimeGPT using nixtlar
This post is a first look at Nixtla’s TimeGPT generative, pre-trained transformer for time series forecasting using the nixtlar R package. As described in Garza et al. (2021), TimeGPT is a Transformer-based time series model with self-attention mechanisms. The architecture comprises an encoder-decoder structure with multiple layers, each with re...
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A First Look at TimeGPT using nixtlar
This post is a first look at Nixtla’s TimeGPT generative, pre-trained transformer for time series forecasting using the nixtlar R package. As described in Garza et al. (2021), TimeGPT is a Transformer-based time series model with self-attention mechanisms. The architecture comprises an encoder-decoder structure with multiple layers, each with re...
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December 2024 Top 40 New CRAN Packages
In December, one hundred twenty-three new packages made it to CRAN. Here are my Top 40 picks in eighteen categories: Agriculture, Biology, Computational Methods, Data, Ecology, Epidemiology, Genomics, Healthcare, Health Technology Assessment, Machine Learning, Medicine, Networks, Statistics, Time Series, Utilities, and Visualization. Agriculture p...
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Bayesian Meta-Analysis with brms
In our previous post, Examining Meta Analysis, we contrasted a frequentist version of a meta analysis conducted with R’s meta package with a Bayesian meta analysis done mostly in stan using the rstan package as a front end. We did this to hint at the difference between working within the restricted confines of a traditional frequentist framework ...
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MMDS 2010
The 2010 Workshop on Algorithms for Modern Massive Data Sets (MMDS 2010) finished up this past Friday (June 18th) at Stanford. This was an exceptionally well organized conference: four days of mind-stretching talks on algorithm development and the challenges of working with massive data sets approached from almost every conceivable angle. The app...
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Why Learn R? It’s the language of Statistics
In the Introduction to his book “R for SAS and SPSS Users” (Springer 2009) Robert Muenchen offers ten reasons for learning R if you already know SAS or SPSS. All ten reasons say something important about R. However, his fourth reason: “R’s language is more powerful than SAS or SPSS. R developers write most of their analytic methods using ...
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Making sense of MapReduce
From guest blogger Joseph Rickert. Last night I went to hear Ken Krugler of Bixolabs talk about Hadoop at the monthly meeting of the Software Developers Forum. Maybe because Ken is an unusually lucid speaker, or maybe because I just reached some sort of cumulative tipping point through the prep work of all those patient people who have tried to h...
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ACM Data Mining Camp
By guest blogger Joseph Rickert. I was very happy to be a part of the ACM Data Mining camp held last Saturday (November 13th) at eBay. It was a big day for discussing hot topics in data mining, Mahout, parallel SVMs etc, and also a pretty big day for R. Because Revolution Analytics was a sponsor for the camp, I got to give a three minute compan...
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