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My primary research interests are Spatial, Bayesian, and Computational Statistics and their application in Environmental and Ecological Sciences.
Marques, I., Wiemann, P. F. and Kneib, T. (2023) A variance partitioning multi-level model for forest inventory data with a fixed plot design. Journal of Agricultural, Biological and Environmental Statistics, (doi: 10.1007/s13253-023-00548-z) (Early Online Publication)
Marques, I., Kneib, T. and Klein, N. (2022) A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes. Statistics and Computing, 32(5), 73. (doi: 10.1007/s11222-022-10136-9)
Marques, I., Kneib, T. and Klein, N. (2022) Mitigating spatial confounding by explicitly correlating Gaussian random fields. Environmetrics, 33(5), e2727. (doi: 10.1002/env.2727)
Marques, I., Klein, N. and Kneib, T. (2020) Non-stationary spatial regression for modelling monthly precipitation in Germany. Spatial Statistics, 40, 100386. (doi: 10.1016/j.spasta.2019.100386)
Marques, I., Wiemann, P. F. and Kneib, T. (2023) A variance partitioning multi-level model for forest inventory data with a fixed plot design. Journal of Agricultural, Biological and Environmental Statistics, (doi: 10.1007/s13253-023-00548-z) (Early Online Publication)
Marques, I., Kneib, T. and Klein, N. (2022) A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes. Statistics and Computing, 32(5), 73. (doi: 10.1007/s11222-022-10136-9)
Marques, I., Kneib, T. and Klein, N. (2022) Mitigating spatial confounding by explicitly correlating Gaussian random fields. Environmetrics, 33(5), e2727. (doi: 10.1002/env.2727)
Marques, I., Klein, N. and Kneib, T. (2020) Non-stationary spatial regression for modelling monthly precipitation in Germany. Spatial Statistics, 40, 100386. (doi: 10.1016/j.spasta.2019.100386)
Lecturer:
