Research Publications for Stephen Joe
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Ejaz, M., Joe, S., & Joshi, C. (2021). Adversarial risk analysis for auctions using mirror equilibrium and Bayes Nash equilibrium. Decision Analysis, 0(0). doi:10.1287/deca.2021.0425
Ejaz, M., Joshi, C., & Joe, S. (2021). Adversarial risk analysis for first-price sealed-bid auctions.. Australian and New Zealand Journal of Statistics, Early View. doi:10.1111/anzs.12315
Brown, P. T., Joshi, C., Joe, S., & Rue, H. (2020). A novel method of marginalisation using low discrepancy sequences for integrated nested Laplace approximations. Computational Statistics & Data Analysis, 107147. doi:10.1016/j.csda.2020.107147
Brown, P., Joshi, C., Joe, S., & Rue, H. (2019). Modified LDS-based methods of marginalisation for integrated nested laplace approximations. In Bayes on the Beach 2019. Gold Coast, Australia.
Joshi, C., Brown, P., & Joe, S. (2017). Bayesian continuous space-time model of burglaries. In 2017 IASC-ARS/NZSA Conference. Conference held at University of Auckland, Auckland, New Zealand..
Joe, S. (2016). The Hermite normal form for certain rank-1 circulant and skew-circulant lattice rules. Linear Algebra and its Applications, 496, 438-451. doi:10.1016/j.laa.2016.02.009
Brown, P. T., Joshi, C., Joe, S., & McCarter, N. (2016). Spatio-temporal modelling of crime using low discrepancy sequences. In 31st International Workshop on Statistical Modelling (IWSM'16). Rennes, France.
Joshi, C., Brown, P. T., & Joe, S. (2016). Using low discrepancy sequences in Grid based Bayesian methods. In 12th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing. Stanford University, California,United States.
Joshi, C., Brown, P., & Joe. (2015). Fast Bayesian Inference using low discrepancy sequences. In Bayes On the Beach Workshop 2015. Conference held at Surfers Paradise, Gold Coast.
Joshi, C., Brown, P. T., & Joe, S. (2015). Low Discrepancy Sequences for faster Bayesian Inference. In University College Dublin (UCD), Dublin, Ireland..