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Homepage Edith Gabriel

Edith GABRIEL

Space time statistics

Senior Researcher

BIOstatistics and Spatial Processes unit

Email: edith.gabriel at inrae.fr

Research interests

Spatio-temporal point processes, Spatial statistics.

Machine learning.

Stochastic geometry.

Kriging.

Estimation of location parameters.

Boundary estimation.

Geometry of random fields.

Ecology, Epidemiology, Forest Fires, Precision agriculture.

Positions

Since 2020: Senior researcher (Directrice de Recherche), INRAE - BioSP unit.

2019 - 2020: Research associate (Chargée de recherche), INRA - BioSP unit.

2014 - 2017: Long term visitor (Délégation recherche), INRA - BioSP unit.

2007 - 2019: Senior lecturer (Maître de Conférences HDR), Avignon University, France.

2005 - 2007: Research Associate, Department of Mathematics and Statistics, Lancaster University, UK.

2004 - 2005: Lecturer in Statistics (ATER), Montpellier II University, France.

Publications

Papers submitted for publication

  • Raeisi M., Bonneu F., Gabriel E. Spatio-temporal hybrid Strauss hardcore point process and application. HAL-03193464

Papers in journals

  • Portes C., Ienco D., Verdin E., Gabriel E. (2024) Environmental and Bio-climatic Data for Epidemiological Analysis over French Mediterranean areas. Environmental Data Science (to appear).
  • Soubeyrand S., Estoup A. et al. (2024) Building integrated plant health surveillance: a proactive research agenda for anticipating and mitigating disease and pest emergence. CABI Agriculture and Bioscience, 5:72. 
  • Ribaud M., Gabriel E., Hughes J., Soubeyrand S. (2023) Identifying potential significant factors impacting zero-inflated proportion data. Statistics in Medicine, 42(19):3467-3486.
  • Gabriel E., Rodriguez-Cortes F, Coville J, Mateu J, Chadoeuf J. (2023) Mapping the intensity function of a non-stationary point process in unobserved areas. Stochastic Environmental Research and Risk Assessment, 37:327--343.
  • Gabriel E., Chadoeuf J. (2022) Note on the approximation of the conditional intensity of non-stationary cluster point processes. Image Analysis and Stereology. 45:1--5.
  • Zamberletti P., Papaïx J., Gabriel E., Opitz T. (2022). Understanding complex spatial dynamics from mechanistic models through spatio-temporal point processes. Ecography. 5:e05956..
  • Zamberletti P. Papaïx, J., Gabriel E., Opitz T. (2021) Markov random field models for vectored-based representations of landscapes. Annals of Applied Statistics, 15(4):1628--1651.
  • Zamberletti P., Sabir, K., Opitz T., Bonnefon O., Gabriel E., Papaïx, J. (2021) More pests but less treatments: ambivalent effect of landscape complexity on Conservation Biological Control. PLOS Computational Biology, 7(11):e1009559
  • Raeisi M., Bonneu F., Gabriel E. (2021) A spatio-temporal multi-scale model for Geyer saturation point process: application to forest fire occurrences. Spatial Statistics, 41:100492.
  • Raeisi M., Bonneu F., Gabriel E. (2020) On spatial and spatio-temporal multi-structure point process models. Les annales de l'ISUP, 63(2-3), 97--114.
  • Opitz T., Bonneu F., Gabriel E. (2020) Point-process based Bayesian modeling of space-time structures of forest fire occurrences in Mediterranean France. Spatial Statistics, 40:100429.
  • Toffin E., Gabriel E., Louis M., Deneubourg J-L., Grégoire J-C. (2018) Colonization of weakened trees by mass attacking bark beetles: no penalty for pioneers, scattered initial distributions and final regular patterns. Scientific Reports, 5(1): 170454.
  • Gabriel E., Coville J., Chadoeuf J. (2017) Estimating the intensity function of spatial point processes outside the observation window. Spatial Statistics, 22, 225--239.
  • Gabriel E., Opitz T., Bonneu F. (2017) Detecting and modeling multi-scale space-time structures: the case of wildfire occurrences. Journal de la Société Francaise de Statistique, 158(3), 86--105.
  • RESSTE Network (2017) Analyzing spatio-temporal data with R: Everything you always wanted to know – but were afraid to ask. Journal de la Société Francaise de Statistique, 158(3), 124--158.
  • Gabriel E. (2017) Book Review: A. Baddeley, E. Rubak, R. Turner. Spatial Point Patterns: Methodology and Applications with R. Mathematical Geosciences, 49(6), 815--817.
  • Gabriel E., Bonneu F., Monestiez P., Chadoeuf J. (2016) Adapted kriging to predict the intensity of partially observed point process data. Spatial Statistics, 18, 54--71.
  • Gaba S., Gabriel E., Chadoeuf J., Bonneu F., Bretagnolle V. (2016) Herbicides do not ensure for higher wheat yield, but eliminate rare plant species. Scientific Reports, 6, 1--10.
  • El Asri M., Blanke D., Gabriel E . (2016) Weighted M-estimators for multivariate clustered data. Statistics and Probability Letters, 112, 26--34.
  • Gabriel E. (2014) Estimating second-order characteristics of inhomogeneous spatio-temporal point process: influence of edge correction methods and intensity estimates. Methodology and Computing in Applied Probability, 16(2), 411--431.
  • Gabriel E., Rowlingson B., Diggle P. (2013) stpp: An R package for plotting, simulating and analysing Spatio-Temporal Point Patterns. Journal of Statistical Software, 53(2), 1--29.
  • Blanke D., Gabriel E., Josselin D. (2012). Comparing new adaptive and robust estimators of location. Les annales de l'ISUP, 56, 65--86.
  • Gabriel E., Allard D., Bacro J-N. (2011). Estimating and testing Zones of Abrupt Change for spatial data. Statistics and Computing, 21, 107--120.
  • Gabriel E., Wilson D., Leatherbarrow H., Cheesbrough J., Gee S., Bolton E., Fox A., Fearnhead P., Hart A., Diggle P. (2010) Spatio-temporal epidemiology of Campylobacter jejuni enteritis, in an area of Northwest England, 2000-2002. Epidemiology and Infection, 138, 1384--1390.
  • Gabriel E., Diggle P. (2009) Second-order analysis of inhomogeneous spatio-temporal point process data. Statistica Neerlandica, 63, 43--51.
  • Wilson D., Gabriel E., Leatherbarrow A., Cheesbrough J., Gee S., Bolton E., Fox A., Hart A., Diggle P., Fearnhead P. (2009) Rapid evolution and the importance of recombination to the gastro-enteric pathogen Campylobacter jejuni. Molecular Biology and Evolution, 26(2), 385--397.
  • Wilson D, Gabriel E., Leatherbarrow A., Cheesbrough J, Gee S., Bolton E., Fox A., Fearnhead P., Diggle P. (2008) Tracing the source of Campylobacteriosis. PLoS Genetics, 4(9):e1000203.
  • Gabriel E., Allard D. (2008). Evaluating the sampling pattern when detecting zones of abrupt change. Environmental and Ecological Statistics, 4, 469--489.
  • Gabriel E., Allard D., Guérif M., Mary B. (2007) Detecting zones of abrupt change in soil data, with an application to an agricultural field. European Journal of Soil Science, 58, 1273--1284.
  • Gabriel E. (2007) Détection de changements abrupts dans le gradient d'un champ gaussien et application aux sciences de l'environnement. Journal de la Société Francaise de Statistique et Revue de Statistique Appliquée, 148, 2, 3--28.

Book chapters

  • Gabriel E. (2016). Spatio-temporal point pattern analysis and modelling. Encyclopedia of GIS, 2nd Edition.
  • Diggle P., Gabriel E. (2010). Spatio-temporal point processes. Handbook of Spatial Statistics. Chapman and Hall/CRC Handbooks of Modern Statistical Methods, pp 449--461.
  • Allard D., Gabriel E. (2007). Détection de zones de changement abrupt pour des variables non permanentes : vers la définition de zones homogènes ? In Agriculture de Précision, Quae, Versailles, pp 165--176.

Others

  • El Asri M., Blanke D., Gabriel E. (2014) Weighted M-estimators for multivariate clustered data: theory and simulation results. arXiv:1412.5136.
  • Gabriel E. (2014). Comprendre et modéliser des phénomènes stochastiques en statistique spatiale et spatio-temporelle. Habilitation thesis, Avignon University, France. Gabriel E., Bonneu F., Monestiez P., Chadoeuf J. (2014) Predicting the intensity of partially observed data from a revisited kriging for point processes. arXiv:1409.6441
  • Gabriel E. (2013) Estimating second-order characteristics of inhomogeneous spatio-temporal point processes: influence of edge correction methods and intensity estimates. arXiv:1304.7178
  • Gabriel E., Diggle P. (2009). Second-order analysis of the spatio-temporal distribution of human campylobacteriosis in Preston, Lancashire. In Atkinson, P.M., Lloyd, C.D. (Eds.). geoENV VII, Geostatistics for Environmental Applications, pp. 99-106.
  • Gabriel E., Allard D. (2005). Assessing the power of zones of abrupt change test detection. In Proceedings of the Seventh International Geostatistical Congress. Kluwer Academic Publisher, pp 1103--1108.
  • Allard D., Gabriel E., Bacro J-N. (2005). Estimating and testing zones of abrupt change for spatial data. Research report.
  • Gabriel E., Allard D., Bacro J-N. (2004). Detecting zones of abrupt change: application to soil data. In X. Sanchez-vila, J. Carrera and R. Froidevaux (Eds.) Proceedings of the 4th European Conference on Geostatistics for Environmental Applications Kluwer Academic Publisher, pp 437-448.
  • Gabriel E. (2004). Détection de zones de changement abrupt dans des données spatiales et application à l'agriculture de précision. Ph.D. thesis, Montpellier University, France.
  • Gabriel E. (2001). Détection de zones de changement abrupt pour un champ gaussien. Master thesis.