April, 2019 | R-bloggers

mlr-2.14.0

April 17, 2019 | r-bloggers on Machine Learning in R

Filters Learners Resampling mlr-org NEWS Roadmap for mlr The last mlr release was in August 2018 - so it was definitely time for a new release after around 9 months of development! The NEWS file can be found directly here. In this post we highligh... [Read more...]

ANCOVA example – April 18, 2019

April 17, 2019 | Chuck Powell

I recently had the need to run an ANCOVA, not a task I perform all that often and my first time using R to do so (I’ve done it in SPSS and SAS before). Having a decent theoretical idea of what I had to do I set off in ... [Read more...]

When Standards Go Wild – Software Review for a Manuscript

April 17, 2019 | rOpenSci - open tools for open science

Stefanie Butland, rOpenSci Community Manager Some things are just irresistible to a community manager – PhD student Hugo Gruson’s recent tweets definitely fall into that category. I was surprised and intrigued to see an example of our software peer review guidelines being used in a manuscript review, independent of our ...

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Explore the landscape of R packages for automated data exploration

April 17, 2019 | smarterpoland

Do you spend a lot of time on data exploration? If yes, then you will like today’s post about AutoEDA written by Mateusz Staniak. If you ever dreamt of automating the first, laborious part of data analysis when you get to know the variables, print descriptive statistics, draw a ... [Read more...]

Bayes vs. the Invaders! Part Three: The Parallax View

April 17, 2019 | tealeaf

The Parallax View In the previous post of this series unveiling the relationship between UFO sightings and population, we crossed the threshold of normality underpinning linear models to construct a generalised linear model based on the more theoretically satisfying Poisson distribution. On inspection, however, this model revealed itself to be... [Read more...]

A Detailed Guide to Plotting Line Graphs in R using ggplot geom_line

April 16, 2019 | Michael Toth

When it comes to data visualization, it can be fun to think of all the flashy and exciting ways to display a dataset. But if you're trying to convey information, flashy isn't always the way to go. In fact, one of the most powerful ways to communicate the relationship between ...

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Tidy correlation tests in R

April 16, 2019 | R on Dominic Royé

When we try to estimate the correlation coefficient between multiple variables, the task is more complicated in order to obtain a simple and tidy result. A simple solution is to use the tidy() function from the {broom} package. In this post we are going to estimate the correlation coefficients between ...

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Setting up RStudio Server on a Cloud for Collaboration and Reproducibility

April 16, 2019 | R Views

Roland Stevenson is a data scientist and consultant who may be reached on Linkedin. When setting up R and RStudio Server on a cloud Linux instance, some thought should be given to implementing a workflow that facilitates collaboration and ensures R project reproducibility. There are many possible workflows to accomplish ...

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Vectorizing functions in R is easy

April 16, 2019 | Roman Luštrik

Imagine you have a function that only takes one argument, but you would really like to work on a vector of values. A short example on how function Vectorize() can accomplish this. Let's say we have a data.frame xy [Read more...]

Vectorizing functions in R is easy

April 16, 2019 | Roman Luštrik

Imagine you have a function that only takes one argument, but you would really like to work on a vector of values. A short example on how function Vectorize() can accomplish this. Let's say we have a data.frame xy [Read more...]

Two interesting facts about high-dimensional random projections

April 16, 2019 | kjytay

John Cook recently wrote an interesting blog post on random vectors and random projections. In the post, he states two surprising facts of high-dimensional geometry and gives some intuition for the second fact. In this post, I will provide R … Continue reading →

$p$

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Controlling Data Layout With cdata

April 16, 2019 | John Mount

Here is an example how easy it is to use cdata to re-layout your data. Tim Morris recently tweeted the following problem (corrected). Please will you take pity on me #rstats folks? I only want to reshape two variables x & y from wide to long! Starting with: d xa xb ...

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Solving the Letterboxed Puzzle in the New York Times

April 15, 2019 | Outsider Data Science

What is the difference between “computer programming” and “data science?” To someone not invovled in either they look much the same. Most data scientists are also coders, though they don’t need to be. Data scientists (especially amateurs like me) don’t...

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Yield curve predictions are really hard

April 15, 2019 | R on OSM

All models are wrong Build the model In the last post, we discussed the yield curve, why investors focus on it, and looked at one measure of the curve – the spread between 10-year and 3-month Treasury yields. In this post, we build a model that...

[Read more...]

Yield curve predictions are really hard

April 15, 2019 | R on OSM

All models are wrong Build the model In the last post, we discussed the yield curve, why investors focus on it, and looked at one measure of the curve – the spread between 10-year and 3-month Treasury yields. In this post, we build a model th...

[Read more...]

Writing a letter to DataCamp

April 15, 2019 | Rstats on Julia Silge

Since 2017 I have been an instructor for DataCamp, the VC-backed online data science education platform. What this means is that I am not an employee, but I have developed content for the company as a contractor. I have two courses there, one on text mining and one on practical supervised ... [Read more...]

Customize Your Interactive EDA: Explore the Fuel Economy of the U.S. Car Market

April 15, 2019 | An Accounting and Data Science Nerd's Corner

Interactive EDA is nice but customized interactive EDA is even nicer. To celebrate the new CRAN version of my ‘ExPanDaR’ package I prepare a customized variant of ‘ExPanD’ to explore the U.S. EPA data on fuel economy. Our objective is to develop an interactive display that guides the reader ...

[Read more...]

Customize Your Interactive EDA: Explore the Fuel Economy of the U.S. Car Market

April 15, 2019 | An Accounting and Data Science Nerd's Corner

Interactive EDA is nice but customized interactive EDA is even nicer. To celebrate the new CRAN version of my ‘ExPanDaR’ package I prepare a customized variant of ‘ExPanD’ to explore the U.S. EPA data on fuel economy. Our objective is to develop an interactive display that guides the reader ...

[Read more...]

Even with randomization, mediation analysis can still be confounded

April 15, 2019 | Keith Goldfeld

Randomization is super useful because it usually eliminates the risk that confounding will lead to a biased estimate of a treatment effect. However, this only goes so far. If you are conducting a meditation analysis in the hopes of understanding the underlying causal mechanism of a treatment, it is important ...

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The sinh-arcsinh normal distribution

April 15, 2019 | kjytay

This month’s issue of Significance magazine has a very nice summary article of the sinh-arcsinh normal distribution. (Unfortunately, the article seems to be behind a paywall.) This distribution was first introduced by Chris Jones and Arthur Pewsey in 2009 as … Continue reading →

$\sigma$

[Read more...]

R-bloggers

R news and tutorials contributed by hundreds of R bloggers

April 2019

mlr-2.14.0

ANCOVA example – April 18, 2019

When Standards Go Wild – Software Review for a Manuscript

Explore the landscape of R packages for automated data exploration

Bayes vs. the Invaders! Part Three: The Parallax View

A Detailed Guide to Plotting Line Graphs in R using ggplot geom_line

Tidy correlation tests in R

Setting up RStudio Server on a Cloud for Collaboration and Reproducibility

Vectorizing functions in R is easy

Vectorizing functions in R is easy

Two interesting facts about high-dimensional random projections

Controlling Data Layout With cdata

Solving the Letterboxed Puzzle in the New York Times

Yield curve predictions are really hard

Yield curve predictions are really hard

Writing a letter to DataCamp

Customize Your Interactive EDA: Explore the Fuel Economy of the U.S. Car Market

Customize Your Interactive EDA: Explore the Fuel Economy of the U.S. Car Market

Even with randomization, mediation analysis can still be confounded

The sinh-arcsinh normal distribution

April 2019

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