Monthly Archives: September 2019

New package: GetQuandlData

September 30, 2019
By
New package: GetQuandlData

Introduction Quandl is one of the best platforms for finding and downloading financial and economic time series. The collection of free databases is solid and I’ve used it intensively in my research and class material. But, a couple of things from the native package Quandl always bothered me: Multiple data is always returned in the wide (column oriented) format (why??); No local caching...

Read more »

EARL London 2019 Conference Recap

September 30, 2019
By
EARL London 2019 Conference Recap

I had an awesome time at the Enterprise Applications of the R Language (EARL) Conference held in London in September, 2019. EARL reminded me that it is good to keep showing up at conferences. I entered and the first thing I heard was organisers at the table welcoming me “Damian is that you? Awesome to Article EARL London 2019...

Read more »

Meetup Recap: Survey and Measure Development in R

September 30, 2019
By
Meetup Recap: Survey and Measure Development in R

Have you ever taken a survey at the doctor or for a job interview and wondered what exactly that data was used for? There is a long-standing series of methodologies, many coming from psychology, on how to reliably measure “latent” traits, such as depression or loyalty, from self-report survey data.  While measurement is a common method in

Read more »

Cleaning Anomalies to Reduce Forecast Error by 9% with anomalize

September 29, 2019
By
Cleaning Anomalies to Reduce Forecast Error by 9% with anomalize

In this tutorial, we’ll show how we used clean_anomalies() from the anomalize package to reduce forecast error by 9%. R Packages Covered: anomalize - Time series anomaly detection Cleaning Anomalies to Reduce Forecast Error by 9% We can often...

Read more »

Fall & Winter Workshop Roundup

September 29, 2019
By
Fall & Winter Workshop Roundup

Join RStudio at one of our Fall and Winter workshops! We’ll be hosting a few different workshops in a variety of cities across the US and UK. Topics range from building tidy tools, to teaching data science, to mastering machine learning. See below for more details on each workshop and how to register. Building Tidy Tools with Hadley Wickham When:...

Read more »

Understanding Bootstrap Confidence Interval Output from the R boot Package

September 29, 2019
By
Understanding Bootstrap Confidence Interval Output from the R boot Package

Nuances of Bootstrapping Most applied statisticians and data scientists understand that bootstrapping is a method that mimics repeated sampling by drawing some number of new samples (with replacement) from the original sample in order to perform inference. However, it can be difficult to understand output from the software that carries out the bootstrapping without a more nuanced understanding of how...

Read more »

More models, more features: what’s new in ‘parameters’ 0.2.0

September 29, 2019
By
More models, more features: what’s new in ‘parameters’ 0.2.0

The easystats project continues to grow, expanding its capabilities and features, and the parameters package 0.2.0 update is now on CRAN. The primary goal of this package is to provide utilities for processing the parameters of various statistical ...

Read more »

bamlss: A Lego Toolbox for Flexible Bayesian Regression

September 29, 2019
By
bamlss: A Lego Toolbox for Flexible Bayesian Regression

Modular R tools for Bayesian regression are provided by bamlss: From classic MCMC-based GLMs and GAMs to distributional models using the lasso or gradient boosting. Citation Umlauf N, Klein N, Simon T, Zeileis A (2019). “baml...

Read more »

Getting started with {golem}

September 29, 2019
By

A little blog post about where to look if you want to get started with {golem}, and an invitation to code with us in October. go-what? If you’ve never heard about it before, {golem} is a tool for building production-grade Shiny applications. With {golem}, Shiny developers have a toolkit for making a stable, easy-to-maintain, and robust for production web...

Read more »

We should buy a VaR

September 28, 2019
By
We should buy a VaR

When you are in 101 of risk management is usual to confuse Bar, VAR and VaR, the first one refers to a place that you should buy (it is a bad idea, do not do it), the second is Vector Autoregressive and the last one Value at Risk, our matter. What is Value at Risk?

Read more »

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)