This post shares short code snippet to make your own screen saver in R, *The Matrix*-style:

# Category: R

## R Journal publication

The R Journal is the open access, refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that should be of interest to users or developers of R.

Christoph Weiss, Gernot Roetzer and myself have joined forces to write an R package and the accompanied paper: **Forecast Combinations in R using the ForecastComb Package**, which is now published in the R journal. Below you can find a few of my thoughts about the journey towards publication in the R journal, and a few words about working with a small team of three, from three different locations.

## R tips and tricks – higher-order functions

A higher-order function is a function that takes one or more functions as arguments, and\or returns a function as its result. This can be super handy in programming when you want to tilt your code towards readability and still keep it concise.

## Reproducible Finance with R – book review

Reproducible Finance with R is a clever book, with modern treatment of classical concepts. Here below is what I liked- and disliked about the book.

## R tips and tricks – the assign() function

The R language has some quirks compared to other languages. One thing which you need to constantly watch for when moving to- or from R, is that R starts its indexing at one, while almost all other languages start indexing at zero, which takes some getting used to. Another quirk is the explicit need for clarity when modifying a variable, compared with other languages.

Take python for example, but I think it looks the same in most common languages:

## R in Finance highlights

The yearly *R in Finance* conference is one of my favorites:

## R tips and tricks – the pipe operator

The R language has improved over the years. Amidst numerous splendid augmentations, the `magrittr`

package by Stefan Milton Bache allows us to write more readable code. It uses an ingenious piping convention which will be explained shortly. This post talks about when to use those pipes, and when to avoid using pipes in your code. I am all about ~~that bass~~ readability, but I am also about speed. Use the pipe operator, but watch the tradeoff.

## R tips and tricks – boxplots for large data

Admit it, you always thought there is something off with how boxplot look like. You can tell there should be some way in which more information can be depicted, they simply look much too spacious. Evidently you are not the only one. Many have tried to suggest better ways to plot the same information. Here on 40 years of boxplots.

## R tips and tricks – the locator function

How many times have you placed the legend in R plot to discover it is being overrun by some points or lines in the chart? Usually what comes next is a trial-and-error phase where you adjust the location, changing the arguments of the x and y coordinates, and re-drawing the plot again to check if the legend or text are now positioned such that they are fully readable.

## R tips and tricks – Set Working Directory

This is more an Rstudio tip than an R tip. It would be nice to know how the following works for different editors, but Rstudio is common enough and awesome enough for the following to be relevant.

## R tips and tricks – Faster Loops

## Insert or bind?

This is the first in a series of planned posts, sharing some R tips and tricks. I hope to cover topics which are not easily found elsewhere. This post has to do with loops in R. There are two ways to save values when looping:

1. You can predefine a vector and fill it, or

2. you can recursively bind the values.

Which one is faster?

## Forecast combinations in R

Few weeks back I gave a talk in the R/Finance 2016 conference, about forecast combinations in R. Here are the slides:

## R vs MATLAB (Round 3)

At least for me, R by faR. MATLAB has its own way of doing things, which to be honest can probably be defended from many angles. Here are few examples for not so subtle differences between R and MATLAB: