The Dantzig Selector in Cox's Proportional Hazards Model, Scandinavian Journal of Statistics, vol.95, issue.4, pp.531-552, 2010. ,
DOI : 10.1093/bioinformatics/18.suppl_1.S120
Primal dual pursuit: A homotopy based algorithm for the Dantzig selector, 2008. ,
On the lasso and dantzig selector equivalence, Information Sciences and Systems (CISS), 2010 44th Annual Conference on, pp.1-6, 2010. ,
Variational estimators for the parameters of Gibbs point process models, Bernoulli, vol.19, issue.3, pp.905-930, 2013. ,
DOI : 10.3150/12-BEJ419
Practical Maximum Pseudolikelihood for Spatial Point Patterns (with Discussion), Australian <html_ent glyph="@amp;" ascii="&"/> New Zealand Journal of Statistics, vol.42, issue.3, pp.283-322, 2000. ,
DOI : 10.1111/1467-842X.00128
Spatstat: An R package for analyzing spatial point pattens, Journal of Statistical Software, vol.12, issue.6, pp.1-42, 2005. ,
DOI : 10.18637/jss.v012.i06
URL : https://doi.org/10.18637/jss.v012.i06
Logistic regression for spatial Gibbs point processes, Biometrika, vol.4, issue.2, pp.377-392, 2014. ,
DOI : 10.1214/10-AOAS331
Spatial Point Patterns: Methodology and Applications with R, 2015. ,
Approximating Point Process Likelihoods with GLIM, Applied Statistics, vol.41, issue.1, pp.31-38, 1992. ,
DOI : 10.2307/2347614
Simultaneous analysis of lasso and Dantzig selector. The Annals of Statistics, pp.1705-1732, 2009. ,
On the central limit theorem for stationary mixing random fields. The Annals of Probability, pp.1047-1050, 1982. ,
Convex optimization, 2004. ,
Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection, The Annals of Applied Statistics, vol.5, issue.1, pp.232-253, 2011. ,
DOI : 10.1214/10-AOAS388
URL : http://doi.org/10.1214/10-aoas388
Better Subset Regression Using the Nonnegative Garrote, Technometrics, vol.37, issue.4, pp.373-384, 1995. ,
DOI : 10.1080/01621459.1980.10477428
Statistics for high-dimensional data: methods, theory and applications, 2011. ,
DOI : 10.1007/978-3-642-20192-9
The Dantzig selector: statistical estimation when p is much larger than n. The Annals of Statistics, pp.2313-2351, 2007. ,
DOI : 10.1214/009053606000001523
URL : http://doi.org/10.1214/009053606000001523
Variational approach for spatial point process intensity estimation, Bernoulli, vol.20, issue.3, pp.1097-1125, 2014. ,
DOI : 10.3150/13-BEJ516
URL : http://doi.org/10.3150/13-bej516
Tropical forest census plots, Landes Company, 1998. ,
DOI : 10.1007/978-3-662-03664-8
Regularized regression methods for variable selection and estimation, 2010. ,
A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point, Journal of the Royal Statistical Society. Series A (Statistics in Society), pp.349-362, 1990. ,
Statistical analysis of spatial and spatio-temporal point patterns, 2013. ,
Least angle regression. The Annals of Statistics, pp.407-499, 2004. ,
Species distribution models: ecological explanation and prediction across space and time. Annual review of ecology, evolution, and systematics, pp.677-697, 2009. ,
DOI : 10.1146/annurev.ecolsys.110308.120159
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties, Journal of the American Statistical Association, vol.96, issue.456, pp.1348-1360, 2001. ,
DOI : 10.1198/016214501753382273
URL : http://www.stat.psu.edu/~rli/research/penlike.pdf
A selective overview of variable selection in high dimensional feature space, Statistica Sinica, vol.20, issue.1, pp.101-148, 2010. ,
Nonconcave penalized likelihood with a diverging number of parameters. The Annals of Statistics, pp.928-961, 2004. ,
Mapping species distributions: spatial inference and prediction, 2010. ,
DOI : 10.1017/CBO9780511810602
Pathwise coordinate optimization, The Annals of Applied Statistics, vol.1, issue.2, pp.302-332, 2007. ,
DOI : 10.1214/07-AOAS131
URL : http://doi.org/10.1214/07-aoas131
The elements of statistical learning, 2008. ,
Regularization Paths for Generalized Linear Models via Coordinate Descent, Journal of Statistical Software, vol.33, issue.1, pp.1-22, 2010. ,
DOI : 10.18637/jss.v033.i01
URL : https://doi.org/10.18637/jss.v033.i01
Second-order analysis of inhomogeneous spatio-temporal point process data, Statistica Neerlandica, vol.39, issue.1, pp.43-51, 2009. ,
DOI : 10.1111/j.1467-9574.2008.00407.x
A Thinned Block Bootstrap Variance Estimation Procedure for Inhomogeneous Spatial Point Patterns, Journal of the American Statistical Association, vol.102, issue.480, pp.1377-1386, 2007. ,
DOI : 10.1198/016214507000000879
A weighted estimating equation approach for inhomogeneous spatial point processes, Biometrika, vol.75, issue.4, pp.867-880, 2010. ,
DOI : 10.1093/biomet/75.4.621
Quasi-likelihood for spatial point processes, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.75, issue.3, pp.677-697, 2015. ,
DOI : 10.1093/biomet/75.4.621
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450110/pdf
Random fields on a network: modeling, statistics, and applications, 1995. ,
Ridge regression. Encyclopedia of statistical sciences, 1988. ,
Light-gap disturbances, recruitment limitation, and tree diversity in a neotropical forest, Science, issue.5401, pp.283554-557, 1999. ,
Barro Colorado forest census plot data, 2005. ,
Robust regression: asymptotics, conjectures and monte carlo. The Annals of Statistics, pp.799-821, 1973. ,
Statistical analysis and modelling of spatial point patterns, 2008. ,
DOI : 10.1002/9780470725160
A generalized Dantzig selector with shrinkage tuning, Biometrika, vol.96, issue.2, pp.323-337, 2009. ,
DASSO: connections between the Dantzig selector and lasso, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.71, issue.1, pp.127-142, 2009. ,
A central limit theorem for mixing random fields, Miskolc Mathematical Notes, vol.7, pp.147-160, 2006. ,
Determinantal point process models and statistical inference, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.4, issue.4, pp.853-877, 2015. ,
DOI : 10.1007/978-1-4612-4628-2
URL : https://hal.archives-ouvertes.fr/hal-01241077
The dantzig selector for censored linear regression models, Statistica Sinica, vol.24, issue.1, p.251, 2014. ,
DOI : 10.5705/ss.2011.220
: Coordinate Descent With Nonconvex Penalties, Journal of the American Statistical Association, vol.106, issue.495, pp.1125-1138, 2011. ,
DOI : 10.1198/jasa.2011.tm09738
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286300/pdf
Discussion: A tale of three cousins: Lasso, l2boosting and Dantzig. The Annals of Statistics, pp.2373-2384, 2007. ,
Structured Spatio-Temporal Shot-Noise Cox Point Process Models, with a View to Modelling Forest Fires, Scandinavian Journal of Statistics, vol.85, issue.1, pp.2-25, 2010. ,
DOI : 10.1007/978-1-4899-3324-9
Aspects of second-order analysis of structured inhomogeneous spatio-temporal point processes, Statistica Neerlandica, vol.39, issue.4, pp.472-491, 2012. ,
DOI : 10.2307/3212829
Statistical inference and simulation for spatial point processes, 2004. ,
DOI : 10.1201/9780203496930
Modern Statistics for Spatial Point Processes, Scandinavian Journal of Statistics, vol.67, issue.0, pp.643-684, 2007. ,
DOI : 10.1093/biomet/85.2.251
A robust hybrid of lasso and ridge regression, Contemporary Mathematics, vol.443, pp.59-72, 2007. ,
Large sample inference for irregularly spaced dependent observations based on subsampling ,
Asymptotic behavior of m-estimators of p regression parameters when p 2 /n is large. I. consistency. The Annals of Statistics, pp.1298-1309, 1984. ,
R: A language and environment for statistical computing. R Foundation for Statistical Computing ,
Asymptotic properties of estimators for the parameters of spatial inhomogeneous Poisson point processes, Advances in Applied Probability, vol.26, pp.122-154, 1994. ,
Advances in presence-only methods in ecology, 2013. ,
Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology, Biometrics, vol.69, issue.1, pp.274-281, 2013. ,
Point process models for presenceonly analysis, Methods in Ecology and Evolution, vol.6, issue.4, pp.366-379, 2015. ,
Adaptive estimation of the intensity of inhomogeneous Poisson processes via concentration inequalities. Probability Theory and Related Fields, pp.103-153, 2003. ,
Consistent parametric estimation of the intensity of a spatial?temporal point process, Journal of Statistical Planning and Inference, vol.128, issue.1, pp.79-93, 2005. ,
Spatio-temporal log-Gaussian Cox processes for modelling wildfire occurrence: the case of Catalonia, 1994???2008, Environmental and Ecological Statistics, vol.18, issue.3, pp.531-563, 1994. ,
DOI : 10.1890/07-0825.1
Statistical analysis of origindestination point patterns: Modeling car thefts and recoveries, 2017. ,
Variable selection for spatial Poisson point processes via a regularization method, Statistical Methodology, vol.17, pp.113-125, 2014. ,
Regularized estimating equations for model selection of clustered spatial point processes, Statistica Sinica, vol.25, issue.1, pp.173-188, 2015. ,
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.58, issue.1, pp.267-288, 1996. ,
Sparsity and smoothness via the fused lasso, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.99, issue.1, pp.91-108, 2005. ,
DOI : 10.1016/S0140-6736(02)07746-2
URL : http://www.stanford.edu/group/SOL/papers/fused-lasso-JRSSB.pdf
An Estimating Function Approach to Inference for Inhomogeneous Neyman-Scott Processes, Biometrics, vol.11, issue.1, pp.252-258, 2007. ,
DOI : 10.1198/108571106X130557
Estimating functions for inhomogeneous spatial point processes with incomplete covariate data, Biometrika, vol.95, issue.2, pp.351-363, 2008. ,
DOI : 10.1093/biomet/asn020
Two-step estimation for inhomogeneous spatial point processes, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.39, issue.3, pp.685-702, 2009. ,
DOI : 10.1017/CBO9780511802256
Analysis of multispecies point patterns by using multivariate log-Gaussian Cox processes, Journal of the Royal Statistical Society: Series C (Applied Statistics), vol.39, issue.1, pp.77-96, 2016. ,
DOI : 10.1111/j.1744-7429.2007.00289.x
Robust Regression Shrinkage and Consistent Variable Selection Through the LAD-Lasso, Journal of Business & Economic Statistics, vol.25, issue.3, pp.347-355, 2007. ,
DOI : 10.1198/073500106000000251
Tuning parameter selectors for the smoothly clipped absolute deviation method, Biometrika, vol.94, issue.3, pp.553-568, 2007. ,
DOI : 10.1093/biomet/asm053
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2663963/pdf
Shrinkage tuning parameter selection with a diverging number of parameters, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.36, issue.3, pp.671-683, 2009. ,
DOI : 10.1111/j.1467-9868.2008.00693.x
High-dimensional variable selection. The Annals of Statistics, pp.2178-2201, 2009. ,
Model selection and estimation in regression with grouped variables, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.58, issue.1, pp.49-67, 2006. ,
DOI : 10.1198/016214502753479356
Variable selection for inhomogeneous spatial point process models, Canadian Journal of Statistics, vol.43, issue.2, pp.288-305, 2015. ,
Nearly unbiased variable selection under minimax concave penalty. The Annals of Statistics, pp.894-942, 2010. ,
DOI : 10.1214/09-aos729
URL : http://doi.org/10.1214/09-aos729
The sparsity and bias of the lasso selection in highdimensional linear regression. The Annals of Statistics, pp.1567-1594, 2008. ,
Regularization Parameter Selections via Generalized Information Criterion, Journal of the American Statistical Association, vol.105, issue.489, pp.312-323, 2010. ,
DOI : 10.1198/jasa.2009.tm08013
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911045/pdf
The Adaptive Lasso and Its Oracle Properties, Journal of the American Statistical Association, vol.101, issue.476, pp.1418-1429, 2006. ,
DOI : 10.1198/016214506000000735
URL : http://cbio.ensmp.fr/~jvert/svn/bibli/local/Zou2006adaptive.pdf
Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005. ,
DOI : 10.1073/pnas.201162998
One-step sparse estimates in nonconcave penalized likelihood models. The Annals of Statistics, pp.1509-1533, 2008. ,
DOI : 10.1214/009053607000000802
URL : http://doi.org/10.1214/009053607000000802
On the adaptive elastic-net with a diverging number of parameters. The Annals of Statistics, pp.1733-1751, 2009. ,
On the ???degrees of freedom??? of the lasso, The Annals of Statistics, vol.35, issue.5, pp.2173-2192, 2007. ,
DOI : 10.1214/009053607000000127