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Understanding the problem by observation.
While the Markov Chain approach seems much like follower data, the approach is different because it is capturing the observed frequencies and normalizing the distribution percentages. This allows capturing a single pick, which can be done in a moving window, allowing for back testing the entire history of each column of each game. From this concept, pick data can be collected and compared to actual results, and an error function can be developed by comparing the pick to the next dra...
Dec 22, 2025, 9:35 am - hypersoniq

$8 on the last PB (1+1)
That has been the only hit so far after dropping out of everything else. The $12/wk budget is the best part... not winning anything is not so interesting. Not wasting my time on dreaming up some system that might help solve the puzzle is super dull... but when you finally see the truth you can't unsee it. My app now is basically a heavily over engineered QP generator. Finally got to use a Markov chain in bioinformatics to calculate transition probabilities for Mendellian inheritance...
Jun 1, 2026, 9:28 am - hypersoniq

Next step for the sums...
So, the vertical sums still need a way to be looked at. I have an idea that will use a rudimentary first order Markov chain... but first I need to apply it to the actual draw numbers. The basic idea is to create a first order Markov model of transition states (such as the observed transition properties of 0 to 9 for each digit in the pick 3 history, accumulating the data to a python dictionary, which will then display the results. Because we know the expectancy, we can spot whe...
Dec 19, 2025, 11:08 am - hypersoniq

Book Idea: Monte Carlo, Random Fields methods in Image Analysis
Title: Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability) (Hardcover) Author: Gerhard Winkler Description: This second edition of G. Winkler's successful book on random field approaches to image analysis, related Markov Chain Monte Carlo methods, and statistical inference with emphasis on Baye...
Feb 9, 2009, 9:50 pm - edge

How the followers are a first order Markov chain...
So the premise is simple... we will stick with the pick 3 to keep it simplified. A follower distribution is simply counting how many times each possible number has followed the last number drawn in each position. In a discrete (only digits 0 through 9) uniform (random, every number has an equal chance to appear next) distribution, if a 6 was drawn, the expected value of each number from 0 to 9 to follow it is 10% When we count each of the digits that has followed a 6...
Jan 2, 2026, 10:59 am - hypersoniq

The script was easy, now comes the hard part...
The script I have dreamed about for several years is finally completed. 100% functioning as intended. Now comes the hard part... interpreting all of the statistics and making a pick. I spent several hours in a discussion with ChatGPT that involved no coding, it was purely about the meaning behind the descriptive statistics. As it would happen, the tail end of each column of data produces a frequency distribution list that is the base calculation required to calculate Markov pr...
Nov 25, 2023, 6:11 am - hypersoniq

The data is the difference
Even in noisy real world bioinformatics data sets there is a structure of biological rules present in the data, even if separated by millions of years of mutations and evolution... lottery data has no guardrails... no underlying truths to build upon. After seeing it work right in front of me on DNA nucleotides, i know that IF the lottery data could be solved, Markov transition chains would have found it......
Jun 3, 2026, 7:25 pm - hypersoniq

A new potential phase 2
While it has been interesting, though not quite so rewarding using the all neutral QP generator in the last few weeks, I have an idea to further process the data in phase one. This would involve building Markov chains using the output and using the resultant Markov probability to narrow down to the neutral that would be most likely to appear in the 7 draw window for each column. I will have to consult the writing on the math version of stack overflow and maybe some R docum...
Aug 17, 2025, 2:02 pm - hypersoniq

Talking shop with Google's Gemini...
Going over some statistical conversations with Google's Gemini the past few days. I like certain aspects better than Chat GPT, such as it references it's sources for further exploration. What resulted is I am planning to add some new data to the output of the classifier script... 1. A row count of how many draws since each number last appeared. This will be used to break ties. 2. Including a chi-square goodness of fit test for the 150 draw window. The P value can...
Aug 19, 2025, 10:14 am - hypersoniq

Something is still missing...
For this year, I moved into gathering follower distributions, basically raw Markov probabilities. The number most likely to follow another in a column is not always right, but sometimes they are. So generating one pick is possible, but it does not win with enough regularity to be interesting. It always seems that the columns are out of phase with each other. The new addition aimed to help fix that by analyzing the raw Markov probabilities of the digits that appear with a locke...
Sep 14, 2024, 3:43 pm - hypersoniq