Coupled connected clusters of the origin for the orthant model
(a 2-dimensional degenerate random environment)
as p changes from 0 to 1.

    Mark Holmes

    Statistics Dept., U. Auckland

    Private Bag 92019

    Auckland 1142, New Zealand

    Phone: +649 3737599 x88679
    Fax:     +649 3737018  



     Curriculum Vitae



The (random) set of vertices that the origin can reach is green.
The set of vertices that can reach the origin is red.
The intersection of the two is blue.

If I have seen less far than others, it is because there are %$#@ing giants with people on their shoulders blocking my view.

ZZZ = the slumber of the beast

The problem with quotes on the internet is that it's hard to verify their authenticity (Abraham Lincoln)

If we ever travel thousands of light years to a planet inhabited by intelligent life, let's just make patterns in their crops and leave.

Two rules to live by: 1) Never tell all that you know

A tongue twister:    This is the atheist anaesthetist's thistle

A partial list of some of my worst jokes: (answers below - disclaimer: some may be culturally dependent, while others are likely to be universally unfunny)
How would you describe the following sequence: abdabdabdabdabdabdabdabd?
Why are adopted children often ignored?
At what time of the year is it possible to successfully mate horses with cattle?

Long time no c
Because they are transparent
Spring equinox

Research interests.

My current interests lie in the realm of random walks, random media (e.g. percolation models), interacting particle systems, measure-valued processes, and applications of probability.

Probability Theory papers

Holmes, M., and Salisbury, T.S.    Random walks in degenerate random environments . Canadian J. of Mathematics - to appear.(pdf)

v.d. Hofstad, R. and Holmes, M.,    The survival probability and r-point functions in high dimensions. Annals of Mathematics 178(2): 665-685, (2013). (pdf)

Holmes, M., and Salisbury, T.S.    Degenerate random environments. Random Structures and Algorithms - to appear. (pdf)

Holmes, M., Sun, R.   A monotonicity property for random walk in a partially random environment. Stochastic Processes and their Applications 122: 1369-1396, 2012. (pdf)

Holmes, M., and Salisbury, T.S.    A combinatorial result with applications to self-interacting random walks. Journal of Combinatorial Theory, Series A 119:460-475, 2012(pdf)

Holmes, M.,   Excited against the tide: A random walk with competing drifts. Annales de l'Institut Henri Poincare Probab. Statist. 48: 745-773, 2012. (pdf)

van der Hofstad, R.,   and    Holmes, M.P.,   An expansion for self-interacting random walks. Brazilian Journal of Probability and Statistics 26:1-55, 2012(pdf)

van der Hofstad, R.,   and    Holmes, M.P.,   Monotonicity for excited random walk in high dimensions. Probability Theory and Related Fields 147:333-348, 2010(pdf)

Holmes, M.P.   The scaling limit of senile reinforced random walk. Electronic Communications in Probability 14:104-115 (2009).(pdf)

van der Hofstad, R.   Holmes, M.P.   and   Slade, G. An extension of the inductive approach to the lace expansion. Electronic Communications in Probability 13:291--301, (2008).(pdf)

Holmes, M.P.,     Convergence of lattice trees to super-Brownian motion above the critical dimension. Electronic J. of Probability 13 (2008) pp671-755(pdf)

Holmes, M.P.,   Sakai, A.,     Senile reinforced random walks. Stochastic Processes and their Applications 117 (2007) pp1519-1539 (pdf)

Holmes, M.P.,   Perkins, E.,   Weak convergence of measure-valued processes and r-point functions.  Annals of Probability 35 (2007) pp1769--1782 (pdf)

Holmes, M.P.,   Jarai, A.A.,   Sakai, A., and Slade, G.   High dimensional graphical networks of self-avoiding walks.  Canad. J. Math. 56:77--114, (2004).(pdf)

Statistics and Applied Probability papers

Holmes, M., Kojadinovic, I., Quessy, J.-F.   Nonparametric tests for change-point detection a la Gombay and Horvath. (pdf) J. of Multivariate Analysis 115, pages 16-32, 2013

Galbraith, S., and Holmes, M.,   A non-uniform birthday problem with applications to discrete logarithms. Discrete Applied Mathematics 160:1547-1560, 2012. (pdf)

Wang, Y., Ziedins, I., Holmes, M. and Challands, N.    Tree-structured Models for Difference and Change Detection in a Complex Environment. Annals of Applied Statistics, 6, 1162-1184. 2012.(pdf)

Chen, Y., Holmes, M., and Ziedins, I.    Monotonicity properties of user equilibrium policies for parallel batch systems. Queueing Systems 70: 81-103, 2012.(pdf)

Kojadinovic, I. and Holmes, M.  Tests of independence among continuous random vectors based on Cramer-von Mises functionals of the empirical copula process.. J. of Multivariate Analysis 100:1137-1154 (2009)(pdf)

Kojadinovic, I., Yan, J. and Holmes, M.   Fast large-sample goodness-of-fit tests for copulas. Statistica Sinica 21:841-871, 2011. (pdf)



Holmes, M., and Salisbury, T.S.    Forward clusters for degenerate random environments. (pdf)

Hofstad, R.v.d., Holmes, M., and Perkins, E.    Criteria for convergence to super-Brownian motion on path space. (pdf)

Hofstad, R.v.d., Holmes, M., Kuznetsov, A., and Ruszel, W.    Strongly reinforced Polya urns with graph-based competition. (pdf)


van der Hofstad, R.,   Holmes, M.,   and   Slade, G.,   Extension of the generalized inductive approach to the lace expansion  (full version in pdf)

Holmes, M.,  and Salisbury, T.S., Speed calculations for random walks in degenerate random environments   (pdf)

aussois slides


UBC Probability


U. Auckland Statistics dept.

An interesting discussion on what student evaluations actually measure



A random walk in a random galaxy far far away

Traffic model with 3 types of particles particles of 3 different speeds arrive as Poisson processes and cannot pass each other

An excited cookie monster

A supercritical senile reinforced random walk with probability one, this walk gets stuck on a single (random) edge.


Site Percolation Defined by a single parameter, p. Bond percolation does not percolate at the critical point in 2 dimensions and above 19 dimensions, what about 3 dimensions? (use arrow keys to change p)

Urn model Defined by a single parameter, p. Starting from one ball of each colour, after you have chosen a red ball n times then there will be (n+1)^p balls of that colour in the urn. Is there a difference between p<1, p>1 and p=1?

The voter model in two dimensions An interacting particle system in which each voter is influenced by their neighbour.