Dr Patrick   Laub

Dr Patrick Laub

Business School
Risk & Actuarial

Patrick Laub is a mathematician & software engineer, and is currently a Lecturer in the School of Risk and Actuarial Studies. He is interested in the intersection of mathematics/statistics and computing, and has previously interned at Google & worked for Data61. His recent research topics include the Empirical Dynamic Modelling, Approximate Bayesian Computation, and Hawkes Processes. Patrick's joint PhD in computational applied probability was completed between the University of Queensland and Aarhus University. For further information, see https://pat-laub.github.io/ .

  • Journal articles | 2018
    Andersen LN; Laub PJ; Rojas-Nandayapa L, 2018, 'Efficient Simulation for Dependent Rare Events with Applications to Extremes', Methodology and Computing in Applied Probability, vol. 20, pp. 385 - 409, http://dx.doi.org/10.1007/s11009-017-9557-4
    Journal articles | 2016
    Laub PJ; Asmussen S; Jensen JL; Rojas-Nandayapa L, 2016, 'Approximating the Laplace transform of the sum of dependent lognormals', Advances in Applied Probability, vol. 48, pp. 203 - 215, http://dx.doi.org/10.1017/apr.2016.50
    Journal articles | 2019
    Asmussen S; Laub P; Yang H, 2019, 'Phase-Type Models in Life Insurance:Fitting and Valuation of Equity-Linked Benefits', Risks, vol. 7, pp. 17 - 17, http://dx.doi.org/10.3390/risks7010017
    Journal articles | 2020
    Goffard P-O; Laub PJ, 2020, 'Orthogonal polynomial expansions to evaluate stop-loss premiums', Journal of Computational and Applied Mathematics, vol. 370, pp. 112648 - 112648, http://dx.doi.org/10.1016/j.cam.2019.112648
    Journal articles | 2018
    Parick L; Robert S; Botev Z, 2018, 'Monte Carlo estimation of the density of the sum of dependent random variables', Mathematics and Computers in Simulation, http://dx.doi.org/10.1016/j.matcom.2018.12.001
  • Preprints | 2018
    Taimre T; Laub PJ, 2018, Rare tail approximation using asymptotics and $L^1$ polar coordinates, http://arxiv.org/abs/1809.06594v1
    Preprints | 2015
    Laub PJ; Taimre T; Pollett PK, 2015, Hawkes Processes, http://arxiv.org/abs/1507.02822v1
    Preprints | 2017
    Asmussen S; Hashorva E; Laub PJ; Taimre T, 2017, Tail asymptotics of light-tailed Weibull-like sums, http://arxiv.org/abs/1712.04070v1
    Preprints | 2017
    Goffard P-O; Laub PJ, 2017, Orthogonal polynomial expansions to evaluate stop-loss premiums, http://arxiv.org/abs/1712.03468v2
    Preprints | 2017
    Laub PJ; Salomone R; Botev ZI, 2017, Monte Carlo Estimation of the Density of the Sum of Dependent Random Variables, http://arxiv.org/abs/1711.11218v2
    Preprints | 2021
    Lee Y; Laub PJ; Taimre T; Zhao H; Zhuang J, 2021, Exact simulation of extrinsic stress-release processes, http://arxiv.org/abs/2106.14415v1
    Preprints | 2020
    Goffard P-O; Laub PJ, 2020, Approximate Bayesian Computations to fit and compare insurance loss models, http://arxiv.org/abs/2007.03833v2
    Preprints | 2020
    Laub PJ; Karoui NE; Loisel S; Salhi Y, 2020, Quickest detection in practice in presence of seasonality: An illustration with call center data, http://arxiv.org/abs/2006.04576v1
    Preprints | 2016
    Andersen LN; Laub PJ; Rojas-Nandayapa L, 2016, Efficient simulation for dependent rare events with applications to extremes, http://arxiv.org/abs/1609.09725v2
    Preprints | 2016
    Asmussen S; Goffard P-O; Laub PJ, 2016, Orthonormal polynomial expansions and lognormal sum densities, http://arxiv.org/abs/1601.01763v1
    Preprints | 2015
    Laub PJ; Asmussen S; Jensen JL; Rojas-Nandayapa L, 2015, Approximating the Laplace transform of the sum of dependent lognormals, http://arxiv.org/abs/1507.03750v2
    Theses / Dissertations |
    Laub P, Computational methods for sums of random variables, http://dx.doi.org/10.14264/uql.2018.748