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Recent content on R Views

  • The reticulate package solves the hardest problem in data science: people

    The reticulate package solves the hardest problem in data science: people

    Andrew Mangano is the Director of eCommerce Analytics at Albertsons Companies. Part I - Modelling The reticulate package integrates Python within R and, when used with RStudio 1.2, brings the two...

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  • Parsnipping Fama French

    Parsnipping Fama French

    Today, we will continue our exploration of developments in the world of tidy models, and we will stick with our usual Fama French modeling flow to do so. For new readers who want get familiar with...

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  • Paid in Books: An Interview with Christian Westergaard

    Paid in Books: An Interview with Christian Westergaard

    R is greatly benefiting from new users coming from disciplines that traditionally did not provoke much serious computation. Journalists1 and humanist scholars2, for example, are embracing R. But,...

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  • Graph analysis using the tidyverse

    Graph analysis using the tidyverse

    It is because I am not a graph analysis expert that I thought it important to write this article. For someone who thinks in terms of single rectangular data sets, it is a bit of a mental leap to...

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  • Some R Packages for ROC Curves

    Some R Packages for ROC Curves

    In a recent post, I presented some of the theory underlying ROC curves, and outlined the history leading up to their present popularity for characterizing the performance of machine learning...

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  • January 2019: “Top 40” New CRAN Packages

    January 2019: “Top 40” New CRAN Packages

    One hundred and fifty-three new packages made it to CRAN in January. Here are my “Top 40” picks in eight categories: Computational Methods, Data, Machine Learning, Medicine, Science, Statistics,...

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  • A Few New R Books

    Greg Wilson is a data scientist and professional educator at RStudio. As a newcomer to R who prefers to read paper rather than pixels, I’ve been working my way through a more-or-less random...

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  • A Look Back on 2018: Part 2

    A Look Back on 2018: Part 2

    Welcome to the second installment of Reproducible Finance 2019! In the previous post, we looked back on the daily returns for several market sectors in 2018. Today, we’ll continue that theme and...

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  • R for Quantitative Health Sciences: An Interview with Jarrod Dalton

    This interview came about through researching R-based medical applications in preparation for the upcoming R/Medicine conference. When we discovered the impressive number of Shiny-based Risk...

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  • December 2018: “Top 40” New CRAN Packages

    December 2018: “Top 40” New CRAN Packages

    By my count, 157 new packages stuck to CRAN in December. Below are my “Top 40” picks in ten categories: Computational Methods, Data, Finance, Machine Learning, Medicine, Science, Statistics, Time...

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  • Onboard and Offboard Data Manipulation in Flexdashboard

    Harrison Schramm is a Professional Statistician and Non-Resident Senior Fellow at the Center for Strategic and Budgetary Assessments. The Shiny set of tools, and, by extension, Flexdashboard,...

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  • ROC Curves

    ROC Curves

    I have been thinking about writing a short post on R resources for working with (ROC) curves, but first I thought it would be nice to review the basics. In contrast to the usual (usual for data...

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  • A Look Back on 2018: Part 1

    A Look Back on 2018: Part 1

    Welcome to Reproducible Finance 2019! It’s a new year, a new beginning, the Earth has completed one more trip around the sun, and that means it’s time to look back on the previous January to...

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  • 2018 R Views Review and Highlights

    2018 was a good year for R Views. With a total of sixty-three posts for the year, we exceeded the pace of at least one post per week. But, it wasn’t quantity we were shooting for. Our main goal...

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  • Rolling Origins and Fama French

    Rolling Origins and Fama French

    Today, we continue our work on sampling so that we can run models on subsets of our data and then test the accuracy of the models on data not included in those subsets. In the machine learning...

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  • November 2018: “Top 40” New Packages

    November 2018: “Top 40” New Packages

    Having absorbed an average of 181 new packages each month over the last 28 months, CRAN is still growing at a pretty amazing rate. The following plot shows the number of new packages since I...

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  • Statistics in Glaucoma: Part III

    Statistics in Glaucoma: Part III

    Samuel Berchuck is a Postdoctoral Associate in Duke University’s Department of Statistical Science and Forge-Duke’s Center for Actionable Health Data Science. Joshua L. Warren is an Assistant...

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  • Rsampling Fama French

    Today we will continue our work on Fama French factor models, but more as a vehicle to explore some of the awesome stuff happening in the world of tidy models. For new readers who want get...

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  • Statistics in Glaucoma: Part II

    Statistics in Glaucoma: Part II

    Samuel Berchuck is a Postdoctoral Associate in Duke University’s Department of Statistical Science and Forge-Duke’s Center for Actionable Health Data Science. Joshua L. Warren is an Assistant...

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  • Statistics in Glaucoma: Part I

    Statistics in Glaucoma: Part I

    Samuel Berchuck is a Postdoctoral Associate in Duke University’s Department of Statistical Science and Forge-Duke’s Center for Actionable Health Data Science. Joshua L. Warren is an Assistant...

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