June, 2019 | R-bloggers

EARL London 2019 evening reception announcement

June 6, 2019 | Mango Solutions

We’ve been to some incredible evening reception venues over the past few years – The Tower of London, HMS Belfast, The Imperial War Museum and a cruise down the Thames! Every year our attendees tell us how valuable the conference networking opportunities are, and our evening reception is the perfect ...

[Read more...]

Downloading Fitbit Data Histories with R

June 5, 2019 | Method Matters

In this post, we will see how to download personal Fitbit data histories for step counts, heart rate, and sleep via the Fitbit API. We will use a combination of existing R packages and custom calls to the Fitbit API to get all of the data we are interested in. ... [Read more...]

Downloading Fitbit Data Histories with R

June 5, 2019 | Method Matters

In this post, we will see how to download personal Fitbit data histories for step counts, heart rate, and sleep via the Fitbit API. We will use a combination of existing R packages and custom calls to the Fitbit API to get all of the data we are interested in.... [Read more...]

Downloading Fitbit Data Histories with R

June 5, 2019 | Method Matters

In this post, we will see how to download personal Fitbit data histories for step counts, heart rate, and sleep via the Fitbit API. We will use a combination of existing R packages and custom calls to the Fitbit API to get all of the data we are interested in.... [Read more...]

Genotype experiments: fitting a stability variance model with R

June 5, 2019 | R on The broken bridge between biologists and statisticians

Yield stability is a fundamental aspect for the selection of crop genotypes. The definition of stability is rather complex (see, for example, Annichiarico, 2002); in simple terms, the yield is stable when it does not change much from one environment to the other. It is an important trait, that helps farmers ... [Read more...]

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

June 5, 2019 | R on easystats

The Problem with Null Effects Say you fit an ANOVA model, predicting the time it takes to solve a puzzle from its shape (round / square) and whether it was colored or black and white, and you found that one of the estimated effects, in this case the interaction, was not ... [Read more...]

Data flow visuals – alluvial vs ggalluvial in R

June 5, 2019 | R on head spin - the Heads or Tails blog

I have long been a fan of creative data visualisation techniques. For me, the choice of visual representation is driven by both the type of data and the kind of question one wants to examine. The power of its visualisation tools has been a major strength of the R language ...

[Read more...]

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

June 5, 2019 | R on easystats

The Problem with Null Effects Say you fit an ANOVA model, predicting the time it takes to solve a puzzle from its shape (round / square) and whether it was colored or black and white, and you found that one of the estimated effects, in this case the interaction, was not ...

[Read more...]

Data flow visuals – alluvial vs ggalluvial in R

June 5, 2019 | R on head spin - the Heads or Tails blog

I have long been a fan of creative data visualisation techniques. For me, the choice of visual representation is driven by both the type of data and the kind of question one wants to examine. The power of its visualisation tools has been a major strength of the R language ...

[Read more...]

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

June 5, 2019 | R on easystats

The Problem with Null Effects Say you fit an ANOVA model, predicting the time it takes to solve a puzzle from its shape (round / square) and whether it was colored or black and white, and you found that one of the estimated effects, in this case the interaction, was not ...

[Read more...]

Genotype experiments: fitting a stability variance model with R

June 5, 2019 | R on The broken bridge between biologists and statisticians

Yield stability is a fundamental aspect for the selection of crop genotypes. The definition of stability is rather complex (see, for example, Annichiarico, 2002); in simple terms, the yield is stable when it does not change much from one environment to the other. It is an important trait, that helps farmers ... [Read more...]

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

June 5, 2019 | R on easystats

The Problem with Null Effects Say you fit an ANOVA model, predicting the time it takes to solve a puzzle from its shape (round / square) and whether it was colored or black and white, and you found that one of the estimated effects, in this case the interaction, was not ...

[Read more...]

Coding Random Forests in 100 lines of code*

June 5, 2019 | André Bleier

In our series of explaining method in 100 lines of code, we tackle random forest this time! We build it from scratch and explore it's functions. Der Beitrag Coding Random Forests in 100 lines of code* erschien zuerst auf STATWORX.

[Read more...]

Simulating Emotions during a Basketball Game – Just a Feeling in the Crowd

June 4, 2019 | R on Will Hipson

Sporting events host witness to a wide range of human emotion. The emotional ups and downs are especially clear among invested fans. Fans experience the joy and excitement of a triumphant comeback, or the anxiety and disappointment of a loss. It is par... [Read more...]

Getting Open Data into R from CKAN

June 4, 2019 | R on Alan Yeung

Preamble Open Data in Scotland Querying CKAN Querying with Custom JSON Querying with SQL Conclusions and Further Ideas Preamble I’ve got lots of rough pieces of R code written as I’ve been exploring/testing various things in the past. A lot of this is currently stored in a ... [Read more...]

Getting Open Data into R from CKAN

June 4, 2019 | R on Alan Yeung

Preamble Open Data in Scotland Querying CKAN Querying with Custom JSON Querying with SQL Conclusions and Further Ideas Preamble I’ve got lots of rough pieces of R code written as I’ve been exploring/testing various things in the past. A lot of this is currently stored in a ... [Read more...]

Simulating Emotions during a Basketball Game – Just a Feeling in the Crowd

June 4, 2019 | R on Will Hipson

Sporting events host witness to a wide range of human emotion. The emotional ups and downs are especially clear among invested fans. Fans experience the joy and excitement of a triumphant comeback, or the anxiety and disappointment of a loss. It is particularly interesting to see how emotions differ from ... [Read more...]

Hybrid Machine Learning Forecasts for the 2019 FIFA Women’s World Cup

June 4, 2019 | Achim Zeileis

Using a random forest ensemble learner we obtain probabilistic forecasts for the FIFA Women's World Cup in France: The clear favorite is defending champion USA followed, with some margin, by host France, England, and Germany. ...

[Read more...]

Email Automation for Google Trends

June 4, 2019 | JOURNEYOFANALYTICS

This blogpost will teach you set up automated email reports to view how search volumes i.e. Google Trends vary over time. The email report will also include important search terms that are “rising” or near a “breakout point”. This can be really useful as the breakout keywords indicate users ...

[Read more...]

AzureR and AzureKeyVault

June 4, 2019 | Hong Ooi

by Hong Ooi, senior data scientist, Microsoft Azure Just a couple of announcements regarding my family of packages for working with Azure from R. First, the packages have moved from the cloudyr org on GitHub to the Azure org, thus making them "official". A (rather spartan) homepage is here, containing ... [Read more...]

R-bloggers

R news and tutorials contributed by hundreds of R bloggers

June 2019

EARL London 2019 evening reception announcement

Downloading Fitbit Data Histories with R

Downloading Fitbit Data Histories with R

Downloading Fitbit Data Histories with R

Genotype experiments: fitting a stability variance model with R

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

Data flow visuals – alluvial vs ggalluvial in R

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

Data flow visuals – alluvial vs ggalluvial in R

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

Genotype experiments: fitting a stability variance model with R

Testing Contrasts from Bayesian Models with ’emmeans’ and ‘bayestestR’

Coding Random Forests in 100 lines of code*

Simulating Emotions during a Basketball Game – Just a Feeling in the Crowd

Getting Open Data into R from CKAN

Getting Open Data into R from CKAN

Simulating Emotions during a Basketball Game – Just a Feeling in the Crowd

Hybrid Machine Learning Forecasts for the 2019 FIFA Women’s World Cup

Email Automation for Google Trends

AzureR and AzureKeyVault

June 2019

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