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Educate-Inspire-Change
Empty Suit
Definition: An amateur who's been given the power to set the goals & objectives for professionals to follow, and thinks of himself as a strong leader.Ethics
"Veritas vos liberabit"
"It's better to build something 100 people love, than something that 1M people kind-of-like" -- Brian Chesky
"Rättvisa handlar inte om lika utfall, utan om lika spelregler" -- Alice Teodorescu
“The mediocre teacher tells. The good teacher explains. The superior teacher demonstrates. The great teacher inspires.” ― William Arthur Ward
When the facts change, I change my mind. What do you do, sir?" -- John Maynard Keynes
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"I do not agree with what you have to say, but I'll defend to the death your right to say it." -- VoltaireSystems view
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Tag Archives: Simulation
Using Bayesian Inference to predict and bet on Italian Serie A Fotball
As my old timer readers know, I’be been using Bayesian Inference to predict and bet on various sporting events, such as FIFA World Cup, and IIHF World Championships. With some success. When the Italian premier division started for about a … Continue reading
Posted in Bayes, Data Analytics, Gambling, Machine Learning, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, Gambling, Machine Learning, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Scipy, Simulation, sports, Statistics, Technology
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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
Posted in Data Analytics, Maritime Technology, Nautical Information Systems, NMEA, Numpy, performance, Python, Simulation, TCPIP
Tagged Communication, Data Analysis, iRegatta2, Network, NMEA, Numpy, performance, programming, Python, Simulation, sports, TCP/IP, Technology
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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
Posted in Bayes, Data Analytics, Data Driven Management, Finance, Gambling, HOCKEY-2018, Math, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, Gambling, HOCKEY-2018, Probability, programming, Python, Science, Simulation, sports, Statistics
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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
Posted in Bayes, Data Analytics, Data Driven Management, Gambling, Math, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, Data Analysis, Gambling, Matplotlib, Numpy, Pandas, Prediction, Probability, PYMC, Python, Simulation, sports, Statistics
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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
Posted in Bayes, Big Business, Big Data, Data Analytics, Gambling, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, Big Business, Data Analysis, Gambling, Matplotlib, Numpy, Probability, PYMC, Python, Simulation, sports, Statistics
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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
Posted in Bayes, Data Analytics, Probability, PYMC, Simulation, Statistics
Tagged Bayes, Data Analysis, LinearRegression, Probability, PYMC, Simulation, Statistics
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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
Posted in Bayes, Data Analytics, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, LinearRegression, Matplotlib, MCMC, Numpy, Pandas, Probability, PYMC, Python, Simulation, Statistics
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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
Posted in Data Analytics, Numpy, Probability, Python, Simulation, Statistics
Tagged Matplotlib, Numpy, Pandas, Python, Simulation, Statistics, Statsmodels
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Val2018 – prognos uppdaterad med opinionssiffrorna för mars [Bayesian Inference]
Inför mars månads prognos har jag gjort flera ändringar i min prognos-modell: Modellen har nu meta-parametrar, i form av en distribution baserad på en uppskattad, subjektiv “valvind” eller “sentiment”, dvs modellen är nu hierarkisk. Modellen bygger nu enbart på de … Continue reading
Posted in Bayes, Data Analytics, Data Driven Management, Politik, PYMC, Python, Simulation, Statistics
Tagged Bayes, Data Analysis, Probability, PYMC, Python, Simulation, Statistics, Val2018
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Distribution of distributions in 3D
Just a quick add-on to my previous post on yet another way to present multidimensional data: To recap, we have a “distribution of distributions”, where each distribution has two dimensions, mu and sigma. In the previous post, I chose to present … Continue reading
Posted in Bayes, Data Analytics, Data Driven Management, Math, Numpy, Probability, Python, Simulation, Statistics
Tagged Bayes, Matplotlib, Numpy, Pandas, Probability, Python, Simulation, Statistics
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