January 2021

Running compiled Stan models in Shiny

January 31, 2021 | R-bloggers | A Random Walk

Introduction The aim of this post is to provide a short step-by-step guide on writing interactive R Shiny-applications that include models written in Stan using rstan and rstantools. The remainder of this post assumes a small amount of working knowledge on writing models in Stan and usage of the package ... [Read more...]

Levies, Tax and the Fuel Price in South Africa

January 31, 2021 | R | datawookie

According to the Automobile Association (AA) the fuel price is the sum of four main components: the basic fuel price the general fuel levy the Road Accident Fund (RAF) levy and wholesale and retail margins, distribution and transport costs. This article suggests that almost 70% of the fuel price in South ...
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Getting data from the Canada Covid-19 Tracker using R

January 31, 2021 | Gavin L. Simpson

Last semester (Fall 2020) I taught a new course in healthcare data science for the Johnson Shoyama Graduate School in Public Policy. One of the final topics of the course was querying application programming interfaces (APIs) from within R. The example we used was querying data on the Covid 19 pandemic from ...
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Predicting blue Gold, ACEA Kaggle challenge

January 31, 2021 | Onno

Blog 2: Data preparation and research question About 2 week ago, yes right around the New year, I was browsing Kaggle just for fun. It made me remember how much fun it actually is to play around with random data. Not only that but very often with a cool purpose too. One ... [Read more...]

Kudos, more is better!

January 31, 2021 | Jimmie

One in the category of Silly Statistics: Yes, I have finished a run, ride or another sporty activity. Let’s share on Strava and hope that people like it and give me kudos. More is better…Continue Reading "Kudos, more is better!"
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Bayesian Model Based Optimization in R

January 30, 2021 | mike

Model-based optimization (MBO) is a smart approach to tuning the hyperparameters of machine learning algorithms with less CPU time and manual effort than standard grid search approaches. The core idea behind MBO is to directly evaluate fewer points within a hyperparameter space, and to instead use a “surrogate model” which ... [Read more...]

Bayesian Model Based Optimization in R

January 30, 2021 | mike

Model-based optimization (MBO) is a smart approach to tuning the hyperparameters of machine learning algorithms with less CPU time and manual effort than standard grid search approaches. The core idea behind MBO is to directly evaluate fewer points within a hyperparameter space, and to instead use a “surrogate model” which ... [Read more...]
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