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Tidy Modeling with R

This is the website for Tidy Modeling with R. This book is a guide to using a new collection of software in the R programming language for model building, and it has two main goals:

  • First and foremost, this book provides an introduction to how to use our software to create models. We focus on a dialect of R called the tidyverse that is designed to be a better interface for common tasks using R. If you’ve never heard of or used the tidyverse, Chapter 2 provides an introduction. In this book, we demonstrate how the tidyverse can be used to produce high quality models. The tools used to do this are referred to as the tidymodels packages.
  • Second, we use the tidymodels packages to encourage good methodology and statistical practice. Many models, especially complex predictive or machine learning models, can work very well on the data at hand but may fail when exposed to new data. Often, this issue is due to poor choices made during the development and/or selection of the models. Whenever possible, our software, documentation, and other materials attempt to prevent these and other pitfalls.


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Lunes, 21 de septiembre de 2020 Sin comentarios

R for Excel Users: Pivot Tables, VLOOKUPs in R

New business and financial analysts are finding R every day. Most of these new userRs (R users) are coming from a non-programming background. They have ample domain experience in functions like finance, marketing, and business, but their tool of choice is Excel (or more recently Tableau & PowerBI)….

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Jueves, 27 de febrero de 2020 Sin comentarios

A simple introduction to programming and statistics with decision trees in R

University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45‐minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields and private industries. However, students unfamiliar with these subjects may be reluctant to join a full course because of time or student workloads or other commitments or a belief it is not for them. The proposed session is short and can be used as an ice‐breaker to let students have a basic understanding of running statistical models in programming language….


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Lunes, 17 de febrero de 2020 Sin comentarios

Animated Plots using ggplot and gganimate

Did you know, that you can transform plain old static ggplot graphs to animated ones? Well you can with the help of the package gganimate by RStudio’s Thomas Lin Pedersen and David Robinson and the results are amazing! My STATWORX colleagues and I are very impressed how effortless all kind of geoms are transformed to suuuper smooth animations. That’s why in this post I will provide a short overview over some of the wonderful functionalities of gganimate, I hope you’ll enjoy them as much as we do!


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Domingo, 16 de febrero de 2020 Sin comentarios

R-INLA review (part II)

The first review was about the main ideas and the approximations itself. This time its a review about the spatial models, see the new  arxiv’ed report.

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Viernes, 23 de febrero de 2018 Sin comentarios


«Our world, our life, our destiny, are dominated by Uncertainty; this is perhaps the only statement we may assert without uncertainty.»

(de Finetti)

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Sábado, 30 de septiembre de 2017 Sin comentarios

NIMBLE: A new way to do MCMC (and more) from BUGS code in R

Interesante … escribir BUGS pero sin utilizar BUGS…


Write statistical models in the BUGS language from R

NIMBLE adopts and extends BUGS as a modeling language and lets you program with the models you create.

Other packages that use the BUGS language are only for Markov chain Monte Carlo (MCMC). With NIMBLE, you can turn BUGS code into model objects and use them for whatever algorithm you want. That includes algorithms provided with NIMBLE and algorithms you write using nimbleFunctions. NIMBLE extends BUGS by allowing multiple parameterizations for distributions, user-written functions and distributions, and more.

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Martes, 5 de julio de 2016 Sin comentarios

Introducing Microsoft R Open

Microsoft poco a poco se va introduciendo en el mundo del R, primero compró Revolutions-Analytics; y ahora ya ofrecve un R server… pues lo último ha sido que RStudio tambien se puede conectar a este server y trabajar contra el.

Introducing Microsoft R Open: Replay and slides

We had a fantastic turnout to last week’s webinar, Introduction to Microsoft R Open. If you missed it, you can watch the replay below. In the talk, I gives some background on the R language and its applications, describe the performance and reproducibility benefits of Microsoft R Open, and give a demonstration of the basics of the R language along with a more in-depth demo of producing a beautiful weather data chart with R.

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Domingo, 7 de febrero de 2016 Sin comentarios

A gentle introduction to parallel computing in R

Una buena introducción.

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Miércoles, 20 de enero de 2016 Sin comentarios

Happy collaboration with Rmd to docx

Os dejo un enlace interesante: This article is reposted from with the kind permission of Richard Layton.


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Jueves, 23 de julio de 2015 Sin comentarios