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prof. dr. P.J.C. (Peter) Spreij

Faculty of Science
Korteweg-de Vries Instituut

Visiting address
  • Science Park 107
  • Room number: F3.35
Postal address
  • Postbus 94248
    1090 GE Amsterdam
Social media
  • Publications




    • Mandjes, M., & Spreij, P. (2017). A note on the central limit theorem for the idleness process in a one-sided reflected Ornstein–Uhlenbeck model. Statistica Neerlandica, 71(3), 225-235. [details]


    • Finesso, L., & Spreij, P. (2016). Factor analysis models via I-divergence optimization. Psychometrika, 81(3), 702-726. [details]
    • Gugushvili, S., & Spreij, P. (2016). Posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient of a stochastic differential equation. ESAIM-Probability and Statistics, 20, 143-153. [details]
    • Huang, G., Jansen, H. M., Mandjes, M., Spreij, P., & De Turck, K. (2016). Markov-modulated Ornstein-Uhlenbeck processes. Advances in Applied Probability, 48(1), 235-254. [details]
    • Huang, G., Mandjes, M., & Spreij, P. (2016). Large deviations for Markov-modulated diffusion processes with rapid switching. Stochastic Processes and their Applications, 126(6), 1785-1818. [details]
    • Mandjes, M., & Spreij, P. (2016). Explicit Computations for Some Markov Modulated Counting Processes. In J. Kallsen, & A. Papapantoleon (Eds.), Advanced Modelling in Mathematical Finance: In Honour of Ernst Eberlein (pp. 63-89). (Springer Proceedings in Mathematics & Statistics; Vol. 189). Cham: Springer. [details]



    • Gugushvili, S., & Spreij, P. (2014). Consistent non-parametric Bayesian estimation for a time-inhomogeneous Brownian motion. ESAIM-Probability and Statistics, 18, 332-341. [details]
    • Gugushvili, S., & Spreij, P. (2014). Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations. Lithuanian Mathematical Journal, 54(2), 127-141. [details]
    • Huang, G., Mandjes, M., & Spreij, P. (2014). Limit theorems for reflected Ornstein-Uhlenbeck processes. Statistica Neerlandica, 68(1), 25-42. [details]
    • Huang, G., Mandjes, M., & Spreij, P. (2014). Weak convergence of Markov-modulated diffusion processes with rapid switching. Statistics & Probability Letters, 86, 74-79. [details]
    • Klein, A., & Spreij, P. (2014). A block Hankel generalized confluent Vandermonde matrix. Linear Algebra and Its Applications, 455, 32-72. [details]
    • van Beek, M., Mandjes, M., Spreij, P., & Winands, E. (2014). Markov switching affine processes and applications to pricing. In M. Vanmaele, G. Deelstra, A. De Schepper, J. Dhaene, W. Schoutens, S. Vanduffel, & D. Vyncke (Eds.), Actuarial and Financial Mathematics Conference, Interplay between Finance and Insurance: February 6-7, 2014 (pp. 97-102). Brussel, België: Koninklijke Vlaamse Academie van België voor Wetenschappen en Kunsten. [details]



    • Gugushvili, S., van Es, B., & Spreij, P. (2011). Deconvolution for an atomic distribution: rates of convergence. Journal of Nonparametric Statistics, 23(4), 1003-1029. [details]
    • Leijdekker, V. J. G., Mandjes, M. R. H., & Spreij, P. J. C. (2011). Sample-path large deviations in credit risk. Journal of applied mathematics, 2011. [details]
    • Leijdekker, V., & Spreij, P. (2011). Explicit computations for a filtering problem with point process observations with applications to credit risk. Probability in the Engineering and Informational Sciences, 25(3), 393-418. [details]
    • Spreij, P., Veerman, E., & Vlaar, P. (2011). An affine two-factor heteroskedastic macro-finance term structure model. Applied Mathematical Finance, 18(4), 331-352. [details]
    • van Es, B., & Spreij, P. (2011). Estimation of a multivariate stochastic volatility density by kernel deconvolution. Journal of Multivariate Analysis, 102(3), 683-697. [details]
    • van Es, B., Spreij, P., & van Zanten, H. (2011). Nonparametric methods for volatility density estimation. In G. di Nunno, & B. Øksendal (Eds.), Advanced Mathematical Methods for Finance (pp. 293-312). (Springer for Research & Development). Berlin - Heidelberg: Springer. [details]


    • Finesso, L., Grassi, A., & Spreij, P. (2010). Approximation of stationary processes by hidden Markov models. Mathematics of control, signals, and systems, 22(1), 1-22. [details]
    • Finesso, L., Grassi, A., & Spreij, P. (2010). Two-step nonnegative matrix factorization algorithm for the approximate realization of hidden Markov models. In A. Edelmayer (Ed.), Proceedings of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary (pp. 369-374). Eötvös Loránd University. [details]
    • Klein, A., & Spreij, P. (2010). Tensor Sylvester matrices and the Fisher information matrix of VARMAX processes. Linear Algebra and Its Applications, 432(8), 1975-1989. [details]



    • Finesso, L., Grassi, A., & Spreij, P. (2008). Approximation of the I-divergence between stationary and hidden Markov processes. In Proceedings of the 2008 International Workshop on Applied Probability (IWAP 2008) Compiègne, France: Université de Technologie de Compiègne. [details]
    • van Es, B., Gugushvili, S., & Spreij, P. (2008). Deconvolution for an atomic distribution. Electronic Journal of Statistics, 2, 265-297. [details]
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Ancillary activities
    • No ancillary activities