Cirad

Nicolas PICARD

Code et programmes

All listings are here.

  1. A criterion based on the Mahalanobis distance for cluster analysis with subsampling. Refer to: N. Picard, A. Bar-Hen. A criterion based on the Mahalanobis distance for cluster analysis with subsampling. Journal of Classification, in press.
  2. Choosing classes for size projection matrix models. Refer to: N. Picard, D. Ouédraogo, A. Bar-Hen. Choosing classes for size projection matrix models. Ecological Modelling, 221(19):2270–2279.
  3. Clustering species using a model of population dynamics and aggregation theory. Refer to: N. Picard, F. Mortier, V. Rossi, S. Gourlet-Fleury (2010). Clustering species using a model of population dynamics and aggregation theory. Ecological Modelling, 221(2):152-160.
  4. Computing the stock recovery rate of tree species using matrix modelling for stage-classified populations. Refer to: N. Picard, L. Ngok Banak, Y. Yalibanda, S. Namkosserena (2009). The stock recovery rate in a Central African rainforest: an index of sustainability based on projection matrix models. Canadian Journal of Forest Research, 39(11):2138-2152.
  5. Finding confidence limits on population growth rates: bootstrap and analytic methods. Refer to: N. Picard, A. Bar-Hen, F. Mortier, P. Chagneau (2009). Finding confidence limits on population growth rates: Bootstrap and analytic methods. Mathematical Biosciences, 219(1):23-31.
  6. Mark-classified and heuristic point processes to model the spatial pattern of trees in tropical rain forests. Refer to: N. Picard, A. Bar-Hen, F. Mortier, J. Chadoeuf (2009). Understainding the dynamics of an undisturbed tropical rain forest from the spatial pattern of trees. Journal of Ecology, 91(1):97-108.
  7. Moments of the stock recovery estimator for hierarchical matrix models, when sample size is driven by a multivariate point process. Refer to: P. Chagneau, F. Mortier, N. Picard (2009). Designing permanent sample plots using a spatially hierarchical matrix population model. Journal of the Royal Statistical Society, Series C (Applied Statistics), 58(3):345-367.
  8. Multi-scale marked area-interaction processes to model the spatial pattern of trees in tropical rain forests. Refer to: N. Picard, A. Bar-Hen, F. Mortier, J. Chadoeuf (2009). The multi-scale marked area-interaction point process: a model for the spatial pattern of trees. Scandinavian Journal of Statistics, 36(1):23-41.
  9. Bootstrap estimates of the moments of the predictions of Usher matrix models. Refer to: N. Picard, Y. Yalibanda, S. Namkosserena, F. Baya (2008). Estimating the stock recovery rate using matrix models. Forest Ecology and Management, 255(10):3597–3605.
  10. Estimator of the intensity of an attractive point process using a distance method. Refer to: N. Picard, A. Bar-Hen (2007). Estimation of the density of a clustered point pattern using a distance method. Environmental and Ecological Statistics, 14(4):341-353.
  11. Estimators of the intensity of a point process using distance methods. Refer to: N. Picard, A. M. Kouyaté, H. Dessard (2005). Tree density estimation using a distance method in Mali savanna. Forest Science, 51(1):7-18.
  12. Indices of dissimilarities between point patterns. Refer to: A. Bar-Hen, N. Picard (2006). Simulation study of dissimilarity between point process. Computational Statistics, 21(3-4):487-507.

Index


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