Blog Archives

Using Modules in R

May 7, 2019
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Using Modules in R

When a code base grows we may think of using several files first and then source them. Functions, of course, are rightfully advocated to new R users, and are the essential building block. Packages are then, already, the next level of abstraction we have to offer....

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ggCorpIdent: Stylize ggplot2 Graphics in Your Corporate Design

March 25, 2019
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ggCorpIdent: Stylize ggplot2 Graphics in Your Corporate Design

This is the add-on to our recently published R Markdown template for business reports. Since we’re working with ggplot2 on a daily basis and use it in nearly every our projects, we designed a ggplot2 theme in our corporate design. That is, it uses our font,...

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R Markdown Template for Business Reports

January 30, 2019
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R Markdown Template for Business Reports

In this post I'd like to introduce the R Markdown template for business reports by INWTlab. It's been my aim to have a nice and clean template that is easy to customize in colors, cover and logo. I know there are quite a few templates available,...

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Cluster Analysis – Part 2: Hands On

November 21, 2018
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Cluster Analysis – Part 2: Hands On

library(broom) library(cluster) library(dplyr) library(ggplot2) library(ggdendro) In the first part of this blog series, we examined the theoretical foundations of cluster analysis. In the following article we put the theory into practice using R. For the analysis in R, we will use the variables mpg (fuel consumption...

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Cluster Analysis – Part 1: Introduction

November 6, 2018
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Cluster Analysis – Part 1: Introduction

What is Cluster Analysis? Cluster analysis is a collective term for various algorithms to find group structures in data. The groups are called clusters and are usually not known a priori. In contrast, classification procedures assign the observations to already...

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Optimize your R Code using Memoization

October 11, 2018
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This article describes how you can apply a programming technique, called Memoization, to speed up your R code and solve performance bottlenecks. Wikipedia says: ...

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Introducing the Kernel Heaping Package III

September 25, 2018
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Introducing the Kernel Heaping Package III

In the second part of this blog series, I showed how to compute spatial kernel density estimates based on area-level data. The Kernelheaping package also supports boundary-corrected kernel density estimation, which allows us to exclude certain areas, where we know that the density must be zero....

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Do GPU-based Basic Linear Algebra Subprograms (BLAS) improve the performance of standard modeling techniques in R?

August 6, 2018
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Do GPU-based Basic Linear Algebra Subprograms (BLAS) improve the performance of standard modeling techniques in R?

Introduction The speed or run-time of models in R can be a critical factor, especially considering the size and complexity of modern datasets. The number of data points as well as the number of features can easily be in...

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Introducing the Kernelheaping Package II

July 13, 2018
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Introducing the Kernelheaping Package II

In the first part of Introducing the Kernelheaping Package I showed how to compute and plot kernel density estimates on rounded or interval censored data using the Kernelheaping package. Now, let’s make a big leap forward to the 2-dimensional case. Interval censoring can be generalised to rectangles or alternatively even arbitrary shapes. That may include counties, zip codes, electoral...

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Design Patterns in R

April 4, 2018
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These notes are inspired by a talk by Stuart Sierra on Design Patterns in Functional Programming and some thoughts I found on F# for fun an profit and are reflection on how I use different strategies to solve things in R. Design Pattern seems...

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