Random [uniform?] sudokus

[This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

A longer run of the R code of yesterday with a million sudokus produced the following qqplot.

It does look ok but no perfect. Actually, it looks very much like the graph of yesterday, although based on a 100-fold increase in the number of simulations. Now, if I test the adequation with a basic chi-square test (!), the result is highly negative:

> chisq.test(obs,p=pdiag/sum(pdiag)) #numerical error in pdiag
Chi-squared test for given probabilities
data:  obs
X-squared = 6978.503, df = 6, p-value < 2.2e-16

(there are seven entries for both obs and pdiag, hence the six degrees of freedom). So this casts a doubt upon the uniformity of the random generator suggested in the paper by Newton and DeSalvo or rather on my programming abilities, see next post!


Filed under: R, Statistics Tagged: combinatorics, entropy, Kullback, Monte Carlo, simulation, sudoku, uniformity

To leave a comment for the author, please follow the link and comment on their blog: Xi'an's Og » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)