Professor of Statistics
Department of Statistics
I am a University Lecturer in Statistics, and also a Fellow of Keble College. This year I lecture on Statistical Theory and Time Series In the Doctoral
Training Centre for Systems Biology I also lecture on Statistical Inference for Networks. Previously
I also lectured on Markov Chain Monte
Carlo and Applied Bayesian Statistics. For course material from previous
years see also a5
Statistics, Part A Statistics
HT2004, b8
Statistics, and Stochastic
Simulation.
On this web site you can find a list of papers, preprints, and talks.
Other professional activities include member of the SemStat steering group, associate editor for Bernoulli, and acting as an associate editor for the Journal of Computational Biology.
Recently I have also become an EPSRC Advanced Fellow in connection with the CABDyN Research Cluster on complex agent-based dynamic networks.
Some general reference sites:
Statistics
Glossary
UCLA Statistics home page; see in
particular for statistical calculators and history of statistics
Virtual Laboratories in
Probability and Statistics
Handout
Lecture notes - note that these cover a somewhat different syllabus:
Peter Clifford's lecture
notes
Mary Lunn's
lecture notes
For regression and ANOVA see also the sections on linear models in Dan Lunn's lecture notes
Proof of Wilks' Theorem
Exercises Sheet 1
Exercises Sheet 2
Exercises Sheet 3
Exercises Sheet 4
Neil Laws' b8 page
Dan Lunn's lecture notes
Problem Sheet 6 Pdf
file Problem Sheet 6
Problem Sheet 7 Pdf
file Problem Sheet 7
Problem Sheet 8 Pdf
file Problem Sheet 8
Problem Sheet 9 Pdf
file Problem Sheet 9
Problem Sheet 10 Pdf
file Problem Sheet 10
Regression
demos
Susan Holmes'
Probability by Surprise page
Hilary Term 2002
Lecture notes Postscript Pdf file
Exercises and Problems 1 Postscript
Exercises and Problems 2 Postscript Pdf file
Exercises and Problems 3 Postscript Pdf file
Exercises and Problems 4 Postscript Pdf file
Practical Postscript
Pdf file
Time Series. Hilary Term 2002. Postscript
Pdf file
Simulation. Michaelmas Term 2002. Pdf file
Michaelmas Term 2002
Lecture 1 and 2 Pdf file
Lecture 3 and 4 Pdf file
Lecture 5 and 6 Pdf file
Lecture 7 and 8 Pdf file
Exercises and Problems 1 Pdf file
Exercises and Problems 2 Pdf file
Exercises and Problems 3 Pdf file
Exercises and Problems 4 Pdf file
S-PLUS Practical Word file
``Solution'' Word file
N.F. Johnson, M. Spagat, S. Gourley, J.-P. Onnela, G. Reinert (2008). Bias in epidemiological studies of conflict mortality. Journal of Peace Research, 45 (5), September 2008, pp.653-663.
P. Chen, C. Deane, G. Reinert (2008). Predicting and validating protein interactions using network structure. PLoS Computational Biology 4 (7): e1000118.Pdf file.
G. Reinert, M.S. Waterman (2008). On the length of the longest exact position match in a Markov sequence. IWAP (International Workshop on Applied Probability) 2008 Conference Proceedings, to appear. Pdf file . Extended version.
P. Eichelsbacher and G. Reinert (2008). Stein's method for discrete Gibbs measures. The Annals of Applied Probability 2008, 18, No. 4, 1588--1618 Pdf file.
G. Reinert and M.S. Waterman (2007). On the length of the longest exact position match in a random sequence. Transactions on Computational Biology and Bioinformatics 4, 153 - 156. Pdf file.
P. Chen, C. Deane, G. Reinert (2007). A statistical approach using network structure in the prediction of protein characteristics. Bioinformatics 23, 2314-2321.Pdf file.
L. Goldstein and G. Reinert (2006). Total Variation Distance for Poisson Subset Numbers.
Annals of Combinatorics (2006), vol 10, 333--341.Pdf file.
A.D. Barbour and G. Reinert (2006).
Discrete small world networks. Electronic
J. Probab. 11,
1234--1283 (2006). Pdf file.
G. Reinert (2005). Three general approaches to Stein's method. In: A Program in Honour of Charles Stein: Tutorial Lecture Notes. A.D. Barbour, L.H.Y. Chen, eds. World Scientific, Singapore (2005), 183-221. Last draft: Pdf file
Goldstein and G. Reinert (2005). Zero biasing in one and higher dimensions, and applications. In: Proceedings of the conference in honor of Charles Stein, A.D. Barbour, L.H.Y. Chen, eds. World Scientific, Singapore (2005), 1-18. Last draft: Pdf file
L. Goldstein and G. Reinert (2005). Distributional transformations, orthogonal polynomials, and Stein characterizations. Jour. Theor. Probab. vol 18, pp185-208. Pdf file
In Russian: Obozr. Prikl. Prom. Mat., (OP&PM Surveys in Applied and Industrial Mathematics) 2006, v. 13, No. 1, pp. 28--50. Pdf file.
G. Reinert, S. Schbath, and M.S. Waterman (2005). Probabilistic and Statistical Properties of Finite Words in Finite Sequences. In: Lothaire: Applied Combinatorics on Words, Cambridge University Press, J. Berstel, D. Perrin, eds. Postscript
S. Holmes and G. Reinert (2004). Stein's method for the bootstrap. In: Stein's Method: Expository Lectures and Applications. IMS Lecture Notes 46, Hayward, P. Diaconis and S. Holmes, eds., 95-133. Pdf
M. Huber and G. Reinert (2004). The stationary distribution in the antivoter model: Exact Sampling and Approximations. In: Stein's Method: Expository Lectures and Applications. IMS Lecture Notes 46, Hayward, P. Diaconis and S. Holmes, eds., 79-93. Postscript
A.D. Barbour and G. Reinert (2003). Small world networks. Extended abstract for MaPhySto and Dynstoch Workshop on Dynamical Stochastic Modelling in Biology, Copenhagen 2003. Pdf file
A.D. Barbour and G. Reinert (2001). Small Worlds. Random Structures and algorithms 19, 54 - 74. Postscript Pdf file
G. Reinert (2001). Stein's method for epidemic processes. In Complex Stochastic Systems. O.E. Barndorff-Nielsen, D.R. Cox and C. Klueppelberg, eds., Chapman and Hall, Boca Raton etc., 235 -275. Postscript Pdf file
A.D. Barbour, R. Gerrard and G. Reinert (2000). Iterates of expanding maps. Probab. Theory Rel. Fields 116, 151 - 180. Postscript Pdf file
G. Reinert, S. Schbath, and M.S. Waterman (2000). Probabilistic and Statistical Properties of Words. J. Comp. Bio. 7, 1 - 46. Postscript Pdf file
G. Reinert (1999). An introduction to Stein's method and application to empirical measures. In Modelos Estocasticos. M.Gonzalez Barrios and L.G.Gorostiza, eds., Sociedad Matematica Mexicana, 65 - 120. (Proceedings of the Symposium on Probability and Stochastic Processes, Guanajuato, Mexico). Postscript Pdf file
G. Reinert and S. Schbath (1999). Compound Poisson approximations for occurrences of multiple words. In Statistics in Molecular Biology and Genetics. F. Seiller-Moiseiwitsch, ed., IMS Lecture Notes, Providence, 257 -275. Postscript
G. Reinert and S. Schbath (1998). Compound Poisson and Poisson process approximations for occurrences of multiple words. J. Comp. Bio. 5, 223 - 253. Postscript
G. Reinert (1998). Couplings for normal approximations with Stein's method. In Microsurveys in Discrete Probability. D. Aldous, J. Propp eds., Dimacs series. AMS, 193 - 207. Postscript Pdf file
L. Goldstein and G. Reinert (1997). Stein's method and the zero bias transformation with application to simple random sampling. Ann. Appl. Probab. 7, 935 - 952. Postscript
L. Goldstein and G. Reinert (1997). Stein's method and the zero bias transformation with application to simple random sampling. USC Technical report. Postscript
R. Arratia, D. Martin, G. Reinert and M. S. Waterman (1996). Poisson approximation for long repeats in a random sequence with application to sequencing by hybridization. J. Comp. Biol. 3, 425 - 463. Postscript
G. Reinert (1995). A weak law of
large numbers for empirical measures via Stein's method. Ann. Probab. 23, 334 -
354.
G. Reinert (1995). The asymptotic evolution
of the General Stochastic Epidemic. Ann. Appl. Probab. 5, 1061 - 1086.
J.-P. Onnela, N. F. Johnson, S. Gourley, G. Reinert, M. Spagat (2008). Sampling bias due to structural heterogeneity and limited internal diffusion. Submitted; available at arXiv:0807.4420v1 [physics.soc-ph].Pdf
A short introduction to Stein's method. Bootstrapping in regular graphs. Statistics for Watts-Strogatz Small World networks. Statistical Inference for Networks: graduate lecture Some
not necessarily useful links Talks