I computed the PageRank vector for the example given in https://en.wikipedia.org/wiki/PageRank (where the picture shows that node B ends up with a score of 38.4, node C with 34.3, node D with 3.9). I implemented the PageRank algorithm, but my numbers are slightly different: 39.8 for node B, and 36.1 for node C, 3.5 for node D, etc). I was wondering if anyone could simulate and obtain the same results they have. My question is what algorithm was used to obtain their numbers.
My algorithm is as follows. Starting with the uniform distribution $r$, I did power iteration using the equation $r = Ar$, where $A = 0.85 M + 0.15 J$, $M$ is the transition matrix of the Web graph given in the example, and $J$ is the matrix whose every entry is $1/N$ ($N=11$ is the number of nodes).