On pagerank

My father is a Statistician, and encountered a nice article on Google Pagerank in one of the occupational magazines.

PageRank was developed in 1998 by the (now very rich) Stanford PhD students Sergey Brin and Larry Page. The vector of page ranks of all web pages in fact follows an equilibrium distribution of an enormous Markov chain.

The hyperlink structure of the web is transformed in transition probabilities. The Markov chain contains all kinds of absorbing states, but PageRank assumes that every user continues with a probability of ? = 0.85 to a another page of the same website, an with a probability of 1 - ? he will enter an arbitrary new URL. This causes the finite, non-periodic Markov chain to be non-reducible, and therefore a equilibrium distribution exists. This equilibrium distribution can be determined numerically by solving a system of linear equations. The enormous size of the state space causes storage problems and numerical problems, but the sparse nature of the matrix helps. The choice of ? = 6/7 is a lucky one from numerical point of view.

– Hayo

Gabriel Mihalache said: on 02 Dec 2005 21:09:24 Statistics is freakishly great! All of the work I'm doing in Microeconomics, Game Theory and Simulations is based on random variables probability distributions, etc.
I think that all these quantitative methods that are used to turn economical theory into models on which hypothesis can be tested are very promising.
Much of the math and statistics that goes into microeconomics work is not part of the work itself but rather allows us to express all these complex processes in a way which can be approached.

PageRank is a great example of people taking mathematical heavy-lifting and the latest in science and putting it to marvelous use.