This is the second post in our series on portfolio volatility, variance and standard deviation. If you missed the first post and want to start at the beginning with calculating portfolio volatility, have a look here - Introduction to Volatility. We will use three objects created in that previous post, so a quick peek is recommended. Today we focus on...
R Documentation at Stack Overflow One of the nice features of R is the ease of data acquisition. I am now working on the examples of data acquisition form different sources within an R session. Soon I am going publish a long-read with an overview of demographic data acquisition in R.
The Ecosystems chapter of my Empirical software engineering book has been added to the draft pdf (download here). I don’t seem to be able to get away from rewriting everything, despite working on the software engineering material for many years. Fortunately the sparsity of the data keeps me in check, but I keep finding new
I’m extremely pleased to announce that the sergeant package is now on CRAN or will be hitting your local CRAN mirror soon. sergeant provides JDBC, DBI and dplyr/dbplyr interfaces to Apache Drill. I’ve also wrapped a few goodies into the dplyr custom functions that work with Drill and if you have Drill UDFs that don’t... Continue reading →
The annual useR!2017 conference took place July 4-7 in Brussels, and in every dimension it was the best yet. It was the largest (with over 1,100 R users from around the world in attendance), and yet still very smoothly run with many amazing talks and lots of fun for everyone. If you weren't able to make it to Brussels,...
Last month the French elections viewed through Twitter: a semantic analysis post showed how the two contenders were perceived on Twitter during three key events of the campaign (Macron leaks, presidential debate and election day). The goal of the post is to show how to perform this twitter analysis using R. Collecting tweets in real time with The post Twitter analysis...
This is the fourth part of the series on volatility modelling. For other parts of the series follow the tag volatility. In this exercise set we will explore GARCH-M and E-GARCH models. We will also use these models to generate rolling window forecasts, bootstrap forecasts and perform simulations. Answers to the exercises are available here. Related exercise sets: Volatility modelling...
In time series analysis, structural changes represent shocks impacting the evolution with time of the data generating process. That is relevant because one of the key assumptions of the Box-Jenkins methodology is that the structure of the data generating process does not change over time. How can structural changes be identified ? The strucchange package Related Post Deep Learning with...
In the modern history, the world has seen unprecedented decrease in human mortality – the result of the Demographic Transition. Initially, the improvements occurred only in the most developed societies, and by the mid XX century the world population was roughly divided in two parts according to mortality patterns (see the bi-modal distribution). After the 2nd World War, the...
One of the many great packages of rOpenSci has implemented the open source engine Tesseract. Optical character recognition (OCR) is used to digitize written or typed documents, i.e. photos or scans of text documents are “translated” into a digital...
Table, Org Chart & Tree Map In the seventh part of our series we are going to learn about the features of some interesting types of charts. More specifically we will talk about Table, Org Chart and Tree Map. Read the examples below to understand the logic of what we are going to do and Related exercise sets: Data Visualization...
Cryptocurrencies are a fascinating phenomenon and excellent data source for analysis with R. This post will introduce how to get a list of available currencies into R. Wikipedia maintains a page with a list of cryptocurrencies. These can be read from HTML into a data frame.library(httr)library(XML)results = GET("https://en.wikipedia.org/wiki/List_of_cryptocurrencies")doc = readHTMLTable(doc=content(results, "text"))View(doc)This list is not complete. Also, an API would...
I have been writing a lot (too much) on the R topics dplyr/rlang/tidyeval lately. The reason is: major changes were recently announced. If you are going to use dplyr well and correctly going forward you may need to understand some of the new issues (if you don’t use dplyr you can safely skip all of … Continue reading dplyr...
The twelveth update in the 0.12.* series of Rcpp landed on CRAN this morning, following two days of testing at CRAN preceded by five full reverse-depends checks we did (and which are always logged in this GitHub repo). The Debian package has been built and uploaded; Windows and macOS binaries should follow at CRAN as usual. This 0.12.12 release...
IntroductionIn the previous post I explored the use of linear model in the forms most commonly used in agricultural research.Clearly, when we are talking about linear models we are implicitly assuming that all relations between the dependent variable y and the predictors x are linear. In fact, in a linear model we could specify different shapes for the relation...
This week’s R bulletin covers some interesting plotting methods. Hope you like this R weekly bulletin. Enjoy reading! Shortcut Keys 1. Source a file – Ctrl+Shift+O 2. Source the current document – Ctrl+Shift+S 3. Find in Files – Ctrl+Shift+F Problem Solving Ideas Using Multiple Colors for Plotting a Variable Plotting a variable with multiple colors... The post R Weekly Bulletin...
Another week, another bunch of Stan updates. Kevin Van Horn and Elea McDonnell Feit put together a tutorial on Stan that covers linear regression, multinomial logistic regression, and hierarchical multinomial logistic regression. Andrew has been working on writing up our “workflow,” by which he means not only the three-step process of Ben Goodrich The post Stan Weekly...
My lightning talk at the useR!2017 conference was R in Minecraft: a five-minute tour of the miner and craft packages and associated book designed to teach kids how to use the R language while manipulating the world of Minecraft. You can see my talk below (starting at the 10:40 mark), and the slides (mostly created in Minecraft) are available...
This is first of the set of exercise on string manipulation with stringr Answers to the exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page. Exercise 1 use a stringr function to merge Related exercise sets: Regular Expressions...
Why should you do this? On Install R and Python via Homebrew I described some potential problems when using R or Python libraries. After doing a fresh OS X install I had some problems with \(\LaTeX\) and XQuartz. The root of the problem is directories location that is easily solved with Homebrew as it doesn't touch the system and provides symlinks...
By the by, I’ve posted a first attempt at an R package – ergastR to wrap the ergast developer API, which is where I get chunks of data from for my f1datajunkie tinkerings. You can find it on Github: psychemedia/ergastR. The function names are the ones used in the Wrangling F1 Data With R book. The
Teaching R to students with little to no experience in programming or data analysis is a challenging task. Our talk at useR!2017 showed how different ingredients of our course Exploratory and Descriptive Data Analysis at UHasselt are used to facilitate … Continue reading →
OpenCPU 2.0 provides the most robust system available today for building and deploying R based apps and services. The server exposes a simple HTTP API for calling with R functions, scripts and managing data, which provides a very solid basi...
A month ago, I started playing with the deep learning framework Keras for R. As a use-case I picked logo detection in images. While the training of a net worked out fine, the results were mediocre. (Check out the full post to for details on the model a...
The presentations and tutorials are starting to become available at the Channel 9 useR!2017 page. There's a wealth of amazing content to explore there already, and I wanted to call out one presentation in particular: Uwe Ligges' keynote presentation, 20 years of CRAN. There are many reasons for the success of R: the language itself, the mathematical and statistical...
Part 2 of 4 in the series Numerical AnalysisPolynomial interpolation is the method of determining a polynomial that fits a set of given points. There are several approaches to polynomial interpolation, of which one of the most well known is the Lagrangian method. This post will introduce the Lagrangian method... The post Lagrangian Polynomial Interpolation with R appeared first on...
