Category Archives: Simulation

Capturing NMEA sentences over WiFi using Python

In order to figure out how the NMEA-WiFi Gateway deals with clients, e.g. if it expects any “handshake” or any other communication setup protocol, I decided to write a simulator mimicing the gateway, and then using iRegatta 2 from Zifago … Continue reading

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Making a living as a Professional Scientific Gambler using Bayesian Inference…?

As my readers know, over the past few weeks I’ve been conducting an experiment: Applying scientific betting on the just finished Ice Hockey World Championships.  By “scientific”, I’m referring to the exclusive use of statistical and mathematical models, simulation, and … Continue reading

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Scientific Gambling – how do betting shops make money….?

Betting shops are commercial businesses, that is, they want to and must make money in order to survive. Like any other business. So take a casino as an example: they make money – in the long run – by having … Continue reading

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Bayesian Inference 2018 Ice Hockey World Cup outcomes

I’ve tuned my Bayesian model a bit. Previously, it used the cumulative sum of historical results point spread as its data input, now it uses each individual game spread. Perhaps an example can make this clearer: Consider two teams, A … Continue reading

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Bayesian Inference – what good is the Prior, anyway…?

A brief example on the effect of Bayesian priors (I’m going to use my Ice Hockey Championship Prediction hack under development for this example): Assume you would like to bet on the outcome of some particular game, for instance, Sweden … Continue reading

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Ice Hockey World Championships 2018 – Baysian inference for predicting results, part II

Just a brief update on my Bayesian model for predicting the upcoming hockey championships. [For info on how to read the graphs below, have a look at part I]. I wrote some scripts to pull in more game results, so … Continue reading

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Predicting the outcome of World Championships in Ice Hockey using Bayesian Inference

Just for fun, I thought I’d implement a Bayesian “statistical inference engine” for some sports tournament. For whatever reason, I came to choose ice hockey world championships, training my inference engine on data from the 2016 tournament, and testing its … Continue reading

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Bayesian Linear Regression with PYMC, part II

In the previous post we looked at a simple linear regression between (simulated) human heights and weights.  In that example, the regression was truly ‘linear’, in that the predictor variable only occured in its first power, to provide a linear regression … Continue reading

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Bayesian Linear Regression with PYMC

Is there a relationship between human height and weight…? Probably. But what does that relationship look like ? Those kinds of questions can be answered by Linear Regression. Below an example, using simulated data for weights,heights etc: import numpy as … Continue reading

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Python,Pandas, Statsmodels: Linear Regression – dealing with categorical data

Sometimes your explanatory variables are not numeric, but categorical. Typical example: “Gender” – which used to be binary, and since I’m an old man, I will continue regarding it as binary… 😉 To handle categorical data in Linear Regression, we … Continue reading

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