How much work is onboarding?

How much work is onboarding?

Our onboarding process, that ensures that packages contributed by the community undergo a transparent, constructive, non adversarial and open review process, involves a lot of work from many actors: authors, reviewers and editors; but how much work? Managing the effort involved in the peer-review process is a major part of ensuring its sustainability and quality. In this post, we’ll take a look at the effort...

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Three Twitter Threads

May 2, 2018
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I've been heads-down this week preparing for some upcoming talks, so not as much blogging as usual this week. But there have been some interesting conversations on Twitter this week that you may be interested to check out if you're not on the platform. Steph Lock shares her go-to R packages for every stage of the data science process:...

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purrr Like a Kitten till the Lake Pipes RoaR

May 2, 2018
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I really should make a minimal effort to resist opening a data analysis blog post with Beach Boys’ lyrics, but this time the combination is too apt. We use the purrr package to show how to let your pipes roar in R. The tidyverse GitHub site contains a simple example illustrating how well pipes and … Continue reading "purrr...

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EARL London Keynote Speaker announcement: Garrett Grolemund

May 2, 2018
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EARL London Keynote Speaker announcement: Garrett Grolemund

...

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Statistical Sins: Is Your Classification Model Any Good?

May 2, 2018
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Statistical Sins: Is Your Classification Model Any Good?

Prediction with Binomial RegressionApril A to Z is complete! We now return to your regularly scheduled statistics blog posts! Today, I want to talk about an issue I touched on during A to Z: using regression to predict values and see how well your model is doing.Specifically, I talked a couple of times about binomial regression (here and...

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Moving to blogdown

May 1, 2018
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Moving to blogdown

I’ve been in the process of transferring my blog (along with creating a personal website) to blogdown, which is hosted on Github Pages. The new blog, or rather, the continuation of this blog, will be at webbedfeet.github.io/posts, and it went live today. I’ll be cross-posting here for a while, at least until Tal gets my

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How efficient are multifactorial experiments?

May 1, 2018
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How efficient are multifactorial experiments?

I recently described why we might want to conduct a multi-factorial experiment, and I alluded to the fact that this approach can be quite efficient. It is efficient in the sense that it is possible to test simultaneously the impact of multiple interventions using an overall sample size that would be required to test a single intervention in a...

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Simulating animal movements and habitat use

Simulating animal movements and habitat use

 Hi there! I was training some ways to simulate animal (or other organisms) movements having into account habitat suitability. To do this, I used my previous eWalk model as the underlying process to simulate random or directional walks. This model is based on Brownian / Ornstein–Uhlenbeck process. You can find more about eWalk model here! Today, I will add one more...

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New introduction article to the R language (in German)

May 1, 2018
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New introduction article to the R language (in German)

About two months ago, the German online magazine 'Informatik Aktuell' asked me to write an introductory article on R. And so I did. It's now only a few days ago that the article was published. It focuses on key concepts of the R language and provi...

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Package ‘quantification’ now on GitHub

May 1, 2018
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My package 'quantification' is now on GitHub: https://github.com/jsugarelli/quantification 'quantification' is a package that provides functions for quantifying qualitative survey data. It supports the Carlson-Parkin method, the regression approac...

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Get your tracks from the Strava API and plot them on Leaflet maps

May 1, 2018
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Get your tracks from the Strava API and plot them on Leaflet maps

Here is some updated R code from my previous post. It doesn't throw any warnings when importing tracks with and without heart rate information. Also, it is easier to distinguish types of tracks now (e.g., when you want to plot runs and rides separately...

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How to do Repeated Measures ANOVAs in R

April 30, 2018
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How to do Repeated Measures ANOVAs in R

Don’t do it The Emotion Dataset The effect of Emotion Post-hoc / Contrast Analysis Interaction Note Credits Don’t do it Ha! Got ya! Trying to run some old school ANOVAs hum? I’ll show you even better! There is now a tremendous amount of data showing the inadequacy of ANOVAs as a statistical procedure (Camilli, 1987; Levy,...

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RcppArmadillo 0.8.500.0

April 30, 2018
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RcppArmadillo 0.8.500.0

RcppArmadillo release 0.8.500.0, originally prepared and uploaded on April 21, has hit CRAN today (after having already been available via the RcppCore drat repo). A corresponding Debian release will be prepared as well. This RcppArmadillo release c...

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17 Jobs for R users from around the world (2018-04-30)

April 30, 2018
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17 Jobs for R users from around the world (2018-04-30)

To post your R job on the next post Just visit  this link and post a new R job  to the R community. You can post a job for  free  (and there are also “featured job” options available for extra exposure). Current R jobs Job seekers:  please follow the links below to learn more and apply for your R job of interest: Featured Jobs...

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Microsoft R Open 3.4.4 now available

April 30, 2018
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An update to Microsoft R Open (MRO) is now available for download on Windows, Mac and Linux. This release upgrades the R language engine to version 3.4.4, which addresses some minor issues with timezone detection and some edge cases in some statistics functions. As a maintenance release, it's backwards-compatible with scripts and packages from the prior release of MRO....

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Make a sculpture in LEGO from a photo, with R

April 30, 2018
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Make a sculpture in LEGO from a photo, with R

The entrance to our office in Redmond in is adorned with this sculpture of our department logo, rendered in LEGO: We had fun with LEGO bricks at work this week. APEX is our internal team name, this was fun. Oh and we're hiring for all roles in Azure! pic.twitter.com/VlNNaTexA5 — Jeff Sandquist (@jeffsand) March 30, 2017 Our team, the...

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Z is for Z-Scores and Standardizing

April 30, 2018
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Z is for Z-Scores and Standardizing

Z is for Z-Scores and StandardizingLast April, I wrapped up the A to Z of Statistics with a post about Z-scores. It seems only fitting that I'm wrapping this April A to Z with the same topic. Z-scores are frequently used, sometimes when you don't even realize it. When you take your child to the doctor and they...

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2018-04 Extreme Makeover: R Graphics Edition

April 29, 2018
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This report describes a complex R graphics customisation example using functions from the ‘grid’ and ‘gridGraphics’ packages and introduces two new functions in ‘grid’: deviceLoc ...

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I’m ‘not in’ right now…

April 29, 2018
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Checking whether an item is in a vector or not in a vector is a common task. The notation in R is a little inelegant when expressing the “not in” condition since the negation operator (!) is separated from the … Continue reading →

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Comparing dependencies of popular machine learning packages with `pkgnet`

April 29, 2018
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Comparing dependencies of popular machine learning packages with `pkgnet`

When looking through the CRAN list of packages, I stumbled upon this little gem: pkgnet is an R library designed for the analysis of R libraries! The goal of the package is to build a graph representation of a package and its dependencies. And I thought it would be fun to play around with it. The little analysis I ended up...

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March 2018: “Top 40” New Package Picks

April 29, 2018
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March 2018: “Top 40” New Package Picks

By my count, just over 200 new packages made it to CRAN and stuck during March. The trend for specialized, and sometimes downright esoteric science packages continues. I counted 40 new packages in this class. Most, but not all of these, are focused on bio-science applications. For example, the foreSIGHT package profiled below focuses on climate science. I was...

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Interpretable Machine Learning with iml and mlr

April 29, 2018
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Interpretable Machine Learning with iml and mlr

Machine learning models repeatedly outperform interpretable, parametric models like the linear regression model. The gains in performance have a price: The models operate as black boxes which are not interpretable. Fortunately, there are many methods that can make machine learning models interpretable. The R package iml provides tools for analysing any black box machine learning model:

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Using Shiny Dashboards for Financial Analysis

April 29, 2018
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Using Shiny Dashboards for Financial Analysis

For some time now, I have been trading traditional assets—mostly U.S. equities. About a year ago, I jumped into the cryptocurrency markets to try my hand there as well. In my time in investor Telegram chats and subreddits, I often saw people arguing over which investments had performed better over time, but the reality was … Continue reading Using...

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Statistics Sunday: Conducting Meta-Analysis in R

April 29, 2018
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Here it is, everyone! The promised 4th post on meta-analysis, and my second video for Deeply Trivial! In this video, I walk through conducting a basic meta-analysis, both fixed and random effects, in the metafor package:See these previous posts and lin...

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Deep Learning from first principles in Python, R and Octave – Part 7

April 29, 2018
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Deep Learning from first principles in Python, R and Octave – Part 7

Artificial Intelligence is the new electricity. – Prof Andrew Ng Most of human and animal learning is unsupervised learning. If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We know how to make the icing … Continue reading Deep...

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Read Random Rows from A Huge CSV File

April 28, 2018
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Given R data frames stored in the memory, sometimes it is beneficial to sample and examine the data in a large-size csv file before importing into the data frame. To the best of my knowledge, there is no off-shelf R function performing such data sampling with a relatively low computing cost. Therefore, I drafted two

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Y is for Ys, Y-hats, and Residuals

April 28, 2018
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Y is for Ys, Y-hats, and Residuals

Y is for Ys, Y-hats, and Residuals When working with a prediction model, like a linear regression, there are a few Ys you need to concern yourself with: the ys (observed outcome variable), the y-hats (predicted outcome variables based on the equation), and the residuals (y minus y-hat). Today, I'll dig into the different flavors of y and...

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Re-exporting the magrittr pipe operator

April 27, 2018
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… or how I stoped worrying and wrote a blog post to remember it ad infinitum. Magrittr’s pipe operator is one of those newish R-universe features that I really want to have around whenever I put some lines into an R-console. This is even TRUE when writing a package. So the first thing I do is put magrittr into the DESCRIPTION...

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ANNOUNCEMENT: EARL London 2018 speakers

April 27, 2018
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ANNOUNCEMENT: EARL London 2018 speakers

We are excited to announce the speakers for this year's EARL London Conference! Every year, we receive an immense number of excellent abstracts and this year was no different - in fact, it's getting harder to decide. We spent a lot of time deliberating and had to make some tough choices. We would like to thank everyone who submitted...

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