https://orcid.org/0000-0002-2660-2865
References
- Brown, P. T., C. Joshi, S. Joe, and H. Rue. 2021. A novel method of marginalisation using low discrepancy sequences for integrated nested Laplace approximations. Computational Statistics & Data Analysis 157:107147. doi: 10.1016/j.csda.2020.107147.
- Cheney, W., and D. Kincaid. 1999. Numerical mathematics and computing. 4th ed. Pacific Grove, CA: ITP.
- Dick, J., and F. Pillichshammer. 2010. Digital nets and sequences. Cambridge: Cambridge University Press.
- Gentle, J. E. 2007. Matrix algebra: Theory, computations and applications in statistics. New York, NY: Springer-Verlag.
- Kress, R. 1998. Numerical analysis. New York, NY: Springer.
- L’Ecuyer, P., and D. Munger. 2016. LatticeBuilder: A general software tool for constructing rank-1 lattice rules. ACM Transactions on Mathematical Software 42 (2):1–30.
- Lemieux, C. 2009. Monte Carlo and quasi-Monte Carlo sampling. New York, NY: Springer.
- Leobacher, G., and F. Pillichshammer. 2014. Introduction to quasi-Monte Carlo integration and applications. Cham: Birkhäuser.
- Martins, T. G., D. Simpson, F. Lindgren, and H. Rue. 2013. Bayesian computing with INLA: New features. Computational Statistics & Data Analysis 67:68–83. doi:10.1016/j.csda.2013.04.014.
- Niederreiter, H. 1992. Random number generation and Quasi-Monte Carlo methods. Vol. 63 of SIAM CBMS-NSF Regional Conference Series in Applied Mathematics, Philadelphia.
- Rue, H., S. Martino, and N. Chopin. 2009. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society - Series B 71 (Part 2):318–92.
- Sloan, I. H., and S. Joe. 1994. Lattice Methods for Multiple Integration. Oxford and New York: Oxford University Press.