Linear programming is a technique to solve optimization problems whose constraints and outcome are represented by linear relationships.Simply put, linear programming allows to solve problems of the following kind:Maximize/minimize $\hat...continue reading.
This is a short post following the previous one (PCA revisited).In this post I’m going to apply PCA to a toy problem: the classification of faces. Again I’ll be working...continue reading.
Principal component analysis (PCA) is a dimensionality reduction technique which might come handy when building a predictive model or in the exploratory phase of your data analysis. It is often...continue reading.
I can’t count how many times I have looked up the formal (measure theoretic) definitions of conditional probability distribution or conditional expectation (even though it’s not that hard :weary:) Another...continue reading.
Thanks to @LukeBornn & Tim Swartz, I had the opportunity to present the #HawkesHand🔥🏀at #CASSIS18 . I learned a lot, had a hell of a time & met some great...continue reading.
Thanks to Rasmus Bååth for some comments and encouragement. When I decided to start my own business doing training in … Morecontinue reading.
She dreams in colour, she dreams in red, can’t find a better man (Better Man, Pearl Jam) Today I bring another experiment based on The Quick Draw! Data from Google, one of...continue reading.
Most SAS procedures require the RUN; statement to signal their termination. However, there are some notable exceptions to this. I have written about PROC SQL many times on my blog,...continue reading.
Abstract: In 2007 Alexander Overwijk went viral with his ‘Perfect Circle’ video. The same year a World Freehand Circle Drawing Championship was organized, which he won. In this post we...continue reading.
This post is in a series that take one image from my book Data Visualization: charts, maps and interactive graphics, … Morecontinue reading.
The co-integration is an important statistical concept behind the statistical arbitrage strategy named “Pairs Trading”. While projecting a stock price with time series models is by all means difficult, it...continue reading.
Introduction It is 35 degree Celsius out side, we are in the middle of the ‘slow news season’, in many countries also called cucumber time. A period typified by the...continue reading.
For More posts on Bayesian models, Bayesian Nonparametrics, and causal inference follow me on twitter @stablemarkets. My advisor and his collaborator are teaching a short course on Bayesian Nonparametric Methods...continue reading.
Abstract: In this post we use R’s capabilities to solve nonlinear equation systems in order to answer an extension of the hanging cable problem to suspension bridges. We then use...continue reading.
I am pleased to welcome Arnab Chakraborty back to my talk show, “The Central Equilibrium“, to talk about the Monty Hall Problem and Bayes’ theorem. In this episode, he shows...continue reading.
Este tutorial tiene como propósito hacer el set-up inicial para empezar a desarrollar modelos machine learning en increíble lenguaje R.continue reading.
Hi, This post is about different ways of using Markov chain Monte Carlo (MCMC) algorithms for numerical integration or sampling. It can be a hard job to design an MCMC...continue reading.
Sydney’s congestion at ‘tipping point’ blares the headline and to illustrate, an interactive chart with bars for city population densities, points for commute times and of course, dual-axes. Yuck. OK,...continue reading.
I love it when researchers take the time to share their knowledge of the computational tools that they use. So first, let me point you at Environmental Computing, a site...continue reading.
In summary: useR! the conference for users of R was held in Brisbane earlier this month it sounded like a lot of fun and here’s an analysis of tweets that...continue reading.
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
