Monthly Archives: June 2018

Why R 2018 Winners

Why R 2018 Winners

How we did it The winners So it’s here… After lots of entries (147 to be precise), we can finally announce the winner of the WhyR 2018 Competition! But first, we have to tell you quickly about how we picked the winner. How we did it So it really wasn’t that hard. We held the questionnaire on typeform. Conveniently, my colleague has created...

Read more »

Extracting a Reference Grid of your Data for Machine Learning Models Visualization

June 24, 2018
By
Extracting a Reference Grid of your Data for Machine Learning Models Visualization

Sometimes, for visualization purposes, we want to extract a reference grid of our dataset. This reference grid often contains equally spaced values of a “target” variable, and all other variables “fixed” by their mean, median or reference level. The refdata of the psycho package was built to do just that. The Model Let’s build a complex machine learning model (a neural...

Read more »

#19: Intel MKL in Debian / Ubuntu follow-up

June 24, 2018
By

Welcome to the (very brief) nineteenth post in the ruefully recalcitrant R reflections series of posts, or R4 for short. About two months ago, in the most recent post in the series, #18, we provided a short tutorial about how to add the Intel Math Kernel Library to a Debian or Ubuntu system thanks to the wonderful apt tool --...

Read more »

Statistics Sunday: Converting Between Effect Sizes for Meta-Analysis

June 24, 2018
By
Statistics Sunday: Converting Between Effect Sizes for Meta-Analysis

Converting Between Effect Sizes I'm currently working on my promised video on mixed effects meta-analysis, and was planning on covering this particular topic in that video - converting between effect sizes. But I decided to do this as a separate post that I can reference in the video, which I hope to post next week.As a brief...

Read more »

Let R/Python send messages when the algorithms are done training

June 24, 2018
By

As Data Scientists, we often train complex algorithms in order to tackle certain business problems and generate value. These algorithms, however, can take a while to train. Sometimes they take a couple of hours, hours which I’m not going to spend just sitting and waiting. But regularly checking whether the training is done, is also

Read more »

Forecasting my weight with R

Forecasting my weight with R

I’ve been measuring my weight almost daily for almost 2 years now; I actually started earlier, but not as consistently. The goal of this blog post is to get re-acquaiented with time series; I haven’t had the opportunity to work with time series for a long time now and I have seen that quite a few packages that deal with time series...

Read more »

A useful forecast combination benchmark

June 23, 2018
By

Forecasting benchmarks are very important when testing new forecasting methods, to see how well they perform against some simple alternatives. Every week I get sent papers proposing new forecasting methods that fail to do better than even the simplest benchmark. They are rejected without review. Typical benchmarks include the naïve method (especially for finance and economic data), the seasonal naïve...

Read more »

A primer in using Java from R – part 1

June 23, 2018
By
A primer in using Java from R – part 1

Introduction This primer shall consist of two parts and its goal is to provide a walk-through of using resources developed in Java from R. It is structured as more of a “note-to-future-self” rather than a proper educational article, I however hope that some readers may still find it useful. It will also list a set of references that I found...

Read more »

future.apply – Parallelize Any Base R Apply Function

June 22, 2018
By
future.apply – Parallelize Any Base R Apply Function

Got compute? future.apply 1.0.0 - Apply Function to Elements in Parallel using Futures - is on CRAN. With this milestone release, all* base R apply functions now have corresponding futurized implementations. This makes it easier than ever before to parallelize your existing apply(), lapply(), mapply(), … code - just prepend future_ to an apply call that takes a...

Read more »

Thanks for Reading!

June 22, 2018
By
Thanks for Reading!

As I've been blogging more about statistics, R, and research in general, I've been trying to increase my online presence, sharing my blog posts in groups of like-minded people. Those efforts seem to have paid off, based on my view counts over the past ...

Read more »

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)