My updated version of my regtools package, tools for parametric and nonparametric regression, is now on CRAN, https://cran.r-project.org/package=regtools It has a number of new functions and datasets. Type vignette(‘regtools’) for an overview. Advertisements
Two years ago I have written a post “Naughty APEs and the quest for the holy grail“, where I have discussed why percentage-based error measures (such as MPE, MAPE, sMAPE) are not good for the task of forecasting performance evaluation. However, it seems to me that I did not explain the topic to the full
In the 1975 edition of “Applied multiple regression/correlation analysis for the behavioral sciences” by Jacob Cohen, an interesting approach of handling missing values in numeric variables was proposed with the purpose to improve the traditional single-value imputation, as described below: – First of all, impute missing values by the value of mean or median –
A new version of graphlayouts is now available on CRAN. This major update introduces several new layout algorithms and adds additional support for weighted networks. Here is a breakdown of all changes: BREAKING CHANGE: removed qgraph(). Now part of ggraph. POSSIBLE BREAKING CHANGE: layout_with_focus() now also returns the distance to the focus node changed filenames (doesn’t have any effect on functionality) added layout_as_dynamic() for longitudinal...
A new version of the RcppExamples package is now on CRAN. The RcppExamples package provides a handful of short examples detailing by concrete working examples how to set up basic R data structures in C++. It also provides a simple example for packagi...
Visualizing the relationship between multiple variables can get messy very quickly. This post is about how the ggpairs() function in the GGally package does this task, as well as my own method for visualizing pairwise relationships when all the variables … Continue reading →
Today’s post comes from an idea and some starting code by my colleague David Diviny from Nous Group. A common real-world problem is trying to estimate an unknown continuous variable from data that has been published in lumped-together bins. Often th...
I recently encountered a situation where I wanted to run several linear models, but where the response variables would depend on previous steps in the data analysis pipeline. Let me illustrate using the mtcars dataset: Let’s say I wanted to … Continue reading →
It’s only been a couple days since the initial version of my revamped take on RSwitch but there have been numerous improvements since then worth mentioning. For starters, there’s a new app icon that uses the blue and gray from the official (modern) R logo to help visually associate it with R: In similar fashion,... Continue reading →
I caught this post on the The Surprising Number Of Programmers Who Can’t Program from the Hacker News RSS feed. Said post links to another, classic post on the same subject and you should read both before continuing. Back? Great! Let’s dig in. Why does hrbrmstr care about this? Offspring #3 completed his Freshman year... Continue reading →
There are a variety of data science courses online, but which one is the best? Find out the pros and cons of each! Coursera, EdX, etc These MOOCs have been around for several years now and continue to grow. But are they really the best option for learning online? Pros: Lots of Topics including R … Continue reading Pros...
Why R? pre-meetings are R meetups that support local R groups. They promote Why R? 2019 Conference. The purpose of those meetings is to provide the space for the professional networking and knowledge exchange, between practitioners and students, from...
How to train and tune machine learning algorithms in a unified way? With mlr R package 😄 I am currently keen on automated machine learning, especially hyperparameter optimization. Therefore, recently I mainly explore frameworks for unified model training. In this post, I will show how to train ML algorithms and tune them using grid-search. I am going to show only...
How to train and tune machine learning algorithms in a unified way? With mlr R package 😄 I am currently keen on automated machine learning, especially hyperparameter optimization. Therefore, recently I mainly focus on frameworks for training models. In this post, I will show how to train ML algorithms and tune them by a grid. I will show only basics,...
Intro In an earlier post, I introduced a function to generate fractals based on regular polygons. In this post I explore doing the same in 3D. library(dplyr) library(plotly) library(RColorBrewer) Fractals in 3D In my previous post on 2D fractals, my function used a formula to generate the starting coordinates for the selected regular polygon. In this case, I have resorted to including the coordinates for...
Background This is a brief post about making my first Shiny App (see also). I made this app following a meeting of the Advancing Social Cognition lab (ASC-Lab) where we discussed this paper by Yzerbyt et al. (2018) proposing a new method for mediation analysis. Any attempt to detail the differences in methods is well beyond the scope of a...
mRpostman is an R package to help you to easy connect to your IMAP (Internet Message Access Protocol) server and execute commands, such as listing mailboxes, searching and fetching messages in a tidy way. It calls ‘curl’ in background when is...
At the bottom of the R for macOS Developer’s Page there’s mention of an “other binary” called “RSwitch” that is “a small GUI that allows you to switch between R versions quickly (if you have multiple versions of R framework installed).” Said switching requires you to use the “tar.gz” versions of R from the R... Continue reading →
What does a modern analytics platform need to offer companies real added value? Why is the administration of user and role rights a factor not to be underestimated when using analytics platforms? In the previous article, we showed how important an intuitive user interface and an open user group concept are for the company-wide use
Since this morning, Rcpp stands at just over 1750 reverse-dependencies on CRAN. The graph on the left depicts the growth of Rcpp usage (as measured by Depends, Imports and LinkingTo, but excluding Suggests) over time. Rcpp was first released in Nove...
In an earlier post I gave a gentle introduction to tidy evaluation in the R tidyverse using simple examples. I covered quoting with enquo and unquoting with !! in brief dplyr and ggplot2 snippets. Today, I aim to build a collection of more complex use cases involving additional tools. Those are our libraries: libs % head(5) ## # A tibble:...
Meeting Hadley! Last Monday, I had the pleasure of attending a talk given by Hadley Wickham at LondonR, which was held at one of their usual venues at the UCL Darwin Lecture Theatre. For most readers of this blog, Hadley needs no introduction: it is...
In this post, we will develop a framework for always-valid inference based on the paper Always Valid Inference: Continuous Monitoring of A/B Tests (2019 Johari, Pekelis, Walsh). Using an always-valid p-value allows us to continuously monitor A/B tests, and potentially stop the test early in a valid way1. In section 5 of the paper, the authors propose their method for...
In this post, I present something I am currently investigating (feedback welcome!) and that I am implementing in my new package {bigutilsr}. This package can be used to detect outlier samples in Principal Component Analysis (PCA). remotes::install_github("privefl/bigutilsr") library(bigutilsr) I present three different statistics of outlierness and two different ways to choose the threshold of being an outlier for those...
Topic Extraction is an integral part of IE (Information Extraction) from Corpus of Text to understand what are all the key things the corpus is talking about. While this can be achieved naively using unigrams and bigrams, a more intelligent way of doing it with an algorithm called RAKE is what we’re going to see in this post. Udpipe udpipe is...
We sent Johannes Tang Kristensen from Arla Foods a few questions about his upcoming talk at EARL London – ‘How much milk do our cows produce? Lessons learned from putting our first R model into production’. How did the need for your project come about? The project started out as part of a larger initiative in Arla with the...
What are driving factors behind the gas price? With freely accessible data we are goging to find out if the brand, the location and more have any impact on the price! Der Beitrag Which Factors Influence Gas Prices? Do Gas Companies Narratives Hold True? erschien zuerst auf STATWORX.
A month ago we closed Call for Papers for Why R? 2019 Conference. Today we are pleased to announce the agenda! From over 75 submissions (from 4 continents) we finally selected 46 presentations (divided into 12 sessions), 15 lightning talks and 9 work...
Introduction This workbook outlines key concepts and functions related to map projections — also referred to as coordinate reference systems (CRSs) — and transformation of geographic data from one projection to another. It is based on the open source book Geocomputation with R, and Chapter 6 in particular. It was developed for the ‘CASA Summer School’, or the Doctoral Summer School for...
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