Harry van Zanten – Vrije Universiteit Amsterdam

Harry van Zanten

Vrije Universiteit Amsterdam

Professor of Statistics at the Mathematics Department of the Vrije Universiteit Amsterdam.

Mailing address:

Prof.dr. J.H. van Zanten
Department of Mathematics
Faculty of Science
Vrije Universiteit
De Boelelaan 1111
1081 HV Amsterdam
The Netherlands

tel: +31 20 5987677
email: j.h.van.zanten AT vu.nl

Visiting address:

NU building (Nieuwe Universiteitsgebouw)
Room 09A67
De Boelelaan 1111
1081 HV Amsterdam
The Netherlands

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Preprints

Szabo, B.T., Vuursteen, L. and van Zanten, J.H. (2022). Optimal high-dimensional and nonparametric distributed testing under communication constraints.
Szabo, B.T. and van Zanten, J.H. (2020). Distributed function estimation: adaptation using minimal communication. To appear in Mathematical Statistics and Learning.

Published papers

2022

Nieman, D., Szabo, B.T. and van Zanten, J.H. (2022).
Contraction rates for sparse variational approximations in Gaussian process regression.
Journal of Machine Learning Research 23(205), 1--26.
Szabo, B.T., Vuursteen, L. and van Zanten, J.H. (2022).
Optimal distributed composite testing in high-dimensional Gaussian models with 1-bit communication.
IEEE Transactions on Information Theory 68(6), 4070--4084.

2021

Hartog, J. and van Zanten, J.H. (2021).
Nonparametric Bayesian label prediction on a large graph using truncated Laplacian regularization. Communications in Statistics – Simulation and Computation 50(12), 3821--383.

2020

Szabo, B.T. and van Zanten, J.H. (2020).
Adaptive distributed methods under communication constraints. Ann. Statist. 48, no. 4, 2347–2380.

2019

Szabo, B.T. and van Zanten, J.H. (2019).
An asymptotic analysis of distributed nonparametric methods. J. Mach. Learn. Res. 20, 1–30.

2018

Kirichenko, A. and van Zanten, J.H. (2018).
Minimax lower bounds for function estimation on graphs. Electron. J. Stat. 12(1), 651-666.
Hartog, J. and van Zanten, J.H. (2018).
Nonparametric Bayesian label prediction on a graph.
Comput. Statist. Data Anal., 120, 111–131.

2017

van der Meulen, F., Schauer, M., van Zanten, J.H. (2017).
Guided proposals for simulating multi-dimensional diffusion bridges.
Bernoulli 23(4A), 2917–2950.
Kirichenko, A., van Zanten, J.H. (2017).
Estimating a smooth function on a large graph by Bayesian Laplacian regularisation.
Electron. J. Stat. 11(1), 891–915.
van Waaij, J. and van Zanten, J.H. (2017).
Full adaptation to smoothness using randomly truncated series priors with Gaussian coefficients and inverse gamma scaling.
Statist. Probab. Lett. 123, 93–99.

2016

Knapik, B.T., Szabo, B.T., van der Vaart, A.W., van Zanten J.H. (2016).
Bayes procedures for adaptive inference in nonparametric inverse problems.
Probab. Theory Related Fields, 164, no.3, 771–813
van Waaij, J. and van Zanten, J.H. (2016).
Gaussian process methods for one-dimensional diffusions: optimal rates and adaptation.
Electron. J. Stat. 10, 628–645.
Sjerps, M.J., Alberink, I., Bolck, A., Stoel, R.D., Vergeer, P. and Van Zanten, J.H. (2016).
Uncertainty and LR: to integrate or not to integrate, that's the question.
Law, Probability and Risk 15, no. 1, 23–29.

2015

Kirichenko, A., van Zanten, J.H. (2015).
Optimality of Poisson processes intensity learning with Gaussian processes.
J. Mach. Learn. Res. 16, 2909–2919.
Szabo, B.T., van der Vaart, A.W., van Zanten J.H. (2015).
Honest Bayesian confidence sets for the L2-norm.
J. Statist. Plann. Inference 166, 36–51.
Belitser, E., Serra, P., van Zanten, J.H. (2015).
Rate-optimal Bayesian intensity smoothing for inhomogeneous Poisson processes.
J. Statist. Plann. Inference 166, 24–35.
Szabo, B.T., van der Vaart, A.W., van Zanten J.H. (2015).
Rejoinder to discussions of “Frequentist coverage of adaptive nonparametric Bayesian credible sets”.
Ann. Statist. 43, no. 4, 1463–1470.
Szabo, B.T., van der Vaart, A.W., van Zanten J.H. (2015).
Frequentist coverage of adaptive nonparametric Bayesian credible sets.
Ann. Statist. 43, no. 4, 1391–1428.

2014

Buishand, A., Jongbloed, G., Klein-Tank, A., Roth, M, Van Zanten, J.H. (2014).
Projections of precipitation extremes based on a regional, non-stationary peaks-over-threshold approach: A case study for the Netherlands and north-western Germany.
Weather and Climate Extremes 4, 1-10.
van der Meulen, F., Schauer, M., van Zanten, J.H. (2014).
Reversible jump MCMC for nonparametric drift estimation for diffusion processes.
Comput. Statist. Data Anal. 71, 615-632.

2013

Belitser, E., Serra, P., van Zanten, J.H. (2013).
Estimating the period of a cyclic non-homogeneous Poisson process.
Scand. J. Statist. 40, no. 2, 204-218.
van Zanten J.H. (2013).
Nonparametric Bayesian methods for one-dimensional diffusion models.
Math. Biosci. 243, no. 2, 215-222.
Szabo, B.T., van der Vaart, A.W., van Zanten J.H. (2013).
Empirical Bayes scaling of Gaussian priors in the white noise model.
Electron. J. Stat. 7, 991-1018.
Knapik, B., van der Vaart, A.W., van Zanten, J.H. (2013).
Bayesian recovery of the initial condition for the heat equation.
Comm. Statist. Theory Methods 42, 1294-1313.
De Jonge, R., van Zanten, J.H. (2013).
Semiparametric Bernstein-Von Mises for the error standard deviation.
Electron. J. Stat. 7, 217-243.
van der Meulen, F., van Zanten, J.H. (2013).
Consistent nonparametric Bayesian inference for discretely observed scalar diffusions.
Bernoulli 19, no.1, 44-63.
Pokern, Y., Stuart, A.M., van Zanten, J.H. (2013).
Posterior consistency via precision operators for Bayesian drift estimation in SDEs.
Stochastic Process. Appl. 123, no. 2, 603-628.

2012

Belitser, E., Ghosal, S., van Zanten, J.H. (2012).
Optimal two-stage procedures for estimating location and size of maximum of multivariate regression functions.
Ann. Statist. 40, no. 6, 2850-2876.
Roth, M., Buishand T.A., Jongbloed, G., Klein Tank, A.M.G., van Zanten, J.H. (2012).
A regional peaks-over-threshold model in a nonstationary climate.
Water Resour. Res. 48, W11533, 12 pp., doi:10.1029/2012WR012214.
De Jonge, R., van Zanten, J.H. (2012).
Adaptive estimation of multivariate functions using conditionally Gaussian tensor-product spline priors.
Electron. J. Stat. 6, 1984-2001.

2011

Knapik, B.T., van der Vaart, A.W., van Zanten, J.H. (2011).
Bayesian inverse problems with Gaussian priors.
Ann. Statist. 39, no. 5, 2626–2657.
van Es, A.J., Spreij, P.J.C., van Zanten, J.H. (2011).
Nonparametric methods for volatility density estimation.
In: Advanced mathematical methods for finance, eds: Di Nunno, Oksendal, pp. 293–312, Springer, Heidelberg.
van der Vaart, A.W., van Zanten, J.H. (2011).
Information Rates of Nonparametric Gaussian Process Methods.
J. Mach. Learn. Res. 12, 2095–2119.
Gasbarra, D., Sottinen, T., van Zanten, J.H. (2011).
Conditional full support of Gaussian processes with stationary increments.
J. Appl. Probab. 48, no. 2, 561–568.

2010

van Zanten, J.H. (2010).
Comments on “PCA based Hurst exponent estimator for fBm signals under disturbances”.
IEEE Trans. Signal Process. 58, no. 8, 4466–4467.
de Jonge, R., van Zanten, J.H. (2010).
Adaptive nonparametric Bayesian inference using location-scale mixture priors.
Ann. Statist. 38, no. 6, 3300–3320.

2009

van Zanten, J.H. (2009).
On Brownian motion as a prior for nonparametric regression.
Statist. Decisions 27, no. 4, 335–356.
Panzar, L., van Zanten, J.H. (2009).
Nonparametric Bayesian inference for ergodic diffusions.
J. Statist. Plann. Inference 139, no. 12, 4193–4199.
van der Vaart, A.W., van Zanten, J.H. (2009).
Adaptive Bayesian estimation using a Gaussian random field with inverse Gamma bandwidth.
Ann. Statist. 37, no. 5B, 2655–2675.
Aurzada, F., Ibragimov, I.A., Lifshits, M.A., van Zanten, J.H (2009).
Small deviations of smooth stationary Gaussian processes.
Theory Probab. Appl. 53 (2009), no. 4, 697–707.

2008

van der Vaart, A.W., van Zanten, J.H. (2008).
Reproducing kernel Hilbert spaces of Gaussian priors.
In: Pushing the limits of contemporary statistics: contributions in honor of Jayanta K. Ghosh, Inst. Math. Stat. Collect., 3, pp. 200–222, Beachwood, OH.
van der Vaart, A.W., van Zanten, J.H. (2008).
Rates of contraction of posterior distributions based on Gaussian process priors.
Ann. Statist. 36, no. 3, 1435–1463.
van Zanten, J.H., Zareba, P. (2008).
A note on wavelet density deconvolution for weakly dependent data.
Stat. Inference Stoch. Process. 11, no. 2, 207–219.
van Zanten, J.H. (2008).
A remark on the equivalence of Gaussian processes.
Electron. Commun. Probab. 13, 54–59.

2007

van der Vaart, A.W., van Zanten, J.H. (2007).
Bayesian inference with rescaled Gaussian process priors.
Electron. J. Stat. 1, 433–448.
van Zanten, J.H. (2007).
When is a linear combination of independent fBm’s equivalent to a single fBm?
Stochastic Process. Appl. 117, no. 1, 57–70.

2006

van der Meulen, F.H., van der Vaart, A.W., van Zanten, J.H. (2006).
Convergence rates of posterior distributions for Brownian semimartingale models.
Bernoulli 12, no. 5, 863–888.
Dzhaparidze, K., van Zanten, J.H., Zareba, P. (2006).
Representations of isotropic Gaussian random fields with homogeneous increments.
J. Appl. Math. Stoch. Anal. 2006, Art. ID 72731, 25 pp.

2005

Dzhaparidze, K., van Zanten, J.H., Zareba, P. (2005).
Representations of fractional Brownian motion using vibrating strings.
Stochastic Process. Appl. 115, no. 12, 1928–1953.
van Zanten, J.H. (2005). On the rate of convergence of the maximum likelihood estimator in Brownian semimartingale models.
Bernoulli 11, no. 4, 643–664.
van der Vaart, A.W., van Zanten, J.H. (2005).
Donsker theorems for diffusions: necessary and sufficient conditions.
Ann. Probab. 33, no. 4, 1422–1451.
Dzhaparidze, K., van Zanten, J.H. (2005).
Optimality of an explicit series expansion of the fractional Brownian sheet.
Statist. Probab. Lett. 71, no. 4, 295–301.
Dzhaparidze, K., van Zanten, J.H. (2005).
Krein’s spectral theory and the Paley-Wiener expansion for fractional Brownian motion.
Ann. Probab. 33, no. 2, 620–644.
van Es, A.J., Spreij, P., van Zanten, J.H. (2005). Nonparametric volatility density estimation for discrete time models. J. Nonparametr. Stat. 17, no. 2, 237–251.

2004

Dzhaparidze, K. (2004), van Zanten, J.H. (2004).
A series expansion of fractional Brownian motion.
Probab. Theory Related Fields 130, no. 1, 39–55.

2003

van Zanten, J.H. (2003). On empirical processes for ergodic diffusions and rates of convergence of M-estimators. Scand. J. Statist. 30, no. 3, 443–458.
van Es, A.J., Spreij, P.J.C., van Zanten, J.H. (2003).
Nonparametric volatility density estimation.
Bernoulli 9, no. 3, 451–465.
van Zanten, J.H. (2003).
On uniform laws of large numbers for ergodic diffusions and consistency of estimators.
Stat. Inference Stoch. Process. 6, no. 2, 199–213.

2002

van Zanten, J.H. (2002). Continuous Ocone martingales as weak limits of rescaled martingales. Electron. Comm. Probab. 7, 215–222 (electronic). With erratum.

2001

van Zanten, J.H. (2001). Rates of convergence and asymptotic normality of kernel estimators for ergodic diffusion processes. J. Nonparametr. Statist. 13, no. 6, 833–850.
van Zanten, J.H. (2001). A note on consistent estimation of multivariate parameters in ergodic diffusion models. Scand. J. Statist. 28, no. 4, 617–623.
Dzhaparidze, K., van Zanten, J.H. (2001).
On Bernstein-type inequalities for martingales.
Stochastic Process. Appl. 93, no. 1, 109–117.

2000

van Zanten, J.H. (2000). On the uniform convergence of the empirical density of an ergodic diffusion. Stat. Inference Stoch. Process. 3, no. 3, 251–262.
Dzhaparidze, K., Spreij, P.J C., van Zanten, J.H. (2000). Some aspects of modeling and statistical inference for financial models. Statist. Neerlandica 54, no. 3, 265–292.
van Zanten, J.H. (2000).
A multivariate central limit theorem for continuous local martingales.
Statist. Probab. Lett. 50, no. 3, 229–235.