Archive for data

data is everywhere

Posted in Kids, pictures, Statistics, University life with tags , , , , , , , , on November 25, 2018 by xi'an

agent-based models

Posted in Books, pictures, Statistics with tags , , , , , , , , on October 2, 2018 by xi'an

An August issue of Nature I recently browsed [on my NUS trip] contained a news feature on agent- based models applied to understanding the opioid crisis in US. (With a rather sordid picture of a drug injection in Philadelphia, hence my own picture.)

To create an agent-based model, researchers first ‘build’ a virtual town or region, sometimes based on a real place, including buildings such as schools and food shops. They then populate it with agents, using census data to give each one its own characteristics, such as age, race and income, and to distribute the agents throughout the virtual town. The agents are autonomous but operate within pre-programmed routines — going to work five times a week, for instance. Some behaviours may be more random, such as a 5% chance per day of skipping work, or a 50% chance of meeting a certain person in the agent’s network. Once the system is as realistic as possible, the researchers introduce a variable such as a flu virus, with a rate and pattern of spread based on its real-life characteristics. They then run the simulation to test how the agents’ behaviour shifts when a school is closed or a vaccination campaign is started, repeating it thousands of times to determine the likelihood of different outcomes.

While I am obviously supportive of simulation based solutions, I cannot but express some reservation at the outcome, given that it is the product of the assumptions in the model. In Bayesian terms, this is purely prior predictive rather than posterior predictive. There is no hard data to create “realism”, apart from the census data. (The article also mixes the outcome of the simulation with real data. Or epidemiological data, not yet available according to the authors.)

In response to the opioid epidemic, Bobashev’s group has constructed Pain Town — a generic city complete with 10,000 people suffering from chronic pain, 70 drug dealers, 30 doctors, 10 emergency rooms and 10 pharmacies. The researchers run the model over five simulated years, recording how the situation changes each virtual day.

This is not to criticise the use of such tools to experiment with social, medical or political interventions, which practically and ethically cannot be tested in real life and working with such targeted versions of the Sims game can paradoxically be more convincing when dealing with policy makers. If they do not object at the artificiality of the outcome, as they often do for climate change models. Just from reading this general public article, I thus wonder at whether model selection and validation tools are implemented in conjunction with agent-based models…

Is nothing > data?

Posted in pictures, Statistics, University life with tags , , , , on July 31, 2017 by xi'an

A fairly interesting take on whether or not data should be singular (an issue that does not occur in French!):

In the Dark

I got this yesterday from one of my office mates who suggested that I stick it somewhere. It’s an advert for a data science company called Pivigo. Logically, the statement on the sticker implies that data is less than nothing, which I don’t think is the point that they’re trying to make. On the other hand, I suppose that by posting this I’ve given Pivigo some free advertising so in some sense it is a successful promotional ploy!

Anyway, when I posted this on Twitter it sparked a little discussion about the vexed issue of whether the word `data’ is singular or plural, so I decided to bore my readers with thoughts on that – not that I’m pedantic or anything.

The word `data’ is formed from the latin plural of the word `datum’ (itself formed from the past participle of the latin verb `dare’, meaning `to give’) hence meaning…

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Paris Machine Learning Meeting #10 Season 2

Posted in Books, Kids, pictures, Statistics, University life with tags , , , , , , , , , , on June 17, 2015 by xi'an

Invalides, Paris, May 8, 2012

Tonight, I am invited to give a speed-presenting talk at the Paris Machine Learning last meeting of Season 2, with the themes of DL, Recovering Robots, Vowpal Wabbit, Predcsis, Matlab, and Bayesian test [by yours truly!] The meeting will take place in Jussieu, Amphi 25, Here are my slides for the meeting:

As it happened, the meeting  was quite crowded with talks and plagued with technical difficulties in transmitting talks from Berlin and Toronto, so I came to talk about three hours after the beginning, which was less than optimal for the most technical presentation of the evening. I actually wonder if I even managed to carry the main idea of replacing Bayes factors with posteriors of the mixture weight! [I had plenty of time to reflect upon this on my way back home as I had to wait for several and rare and crowded RER trains until one had enough room for me and my bike!]