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Inference for low‐ and high‐dimensional inhomogeneous Gibbs point processes. (2023). Coeurjolly, Jeanfranois ; Ba, Ismala.
In: Scandinavian Journal of Statistics.
RePEc:bla:scjsta:v:50:y:2023:i:3:p:993-1021.

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  1. Ba, I., & Coeurjolly, J.‐F. (2022a). Short tutorial related to the paper “Inference for low and high dimensional inhomogeneous Gibbs point processes”. Scandinavian Journal of Statistics.
    Paper not yet in RePEc: Add citation now
  2. Ba, I., & Coeurjolly, J.‐F. (2022b). Supplement to “Inference for low and high dimensional inhomogeneous Gibbs point processes”. Scandinavian Journal of Statistics.
    Paper not yet in RePEc: Add citation now
  3. Baddeley, A., & Turner, R. (2000). Practical maximum pseudolikelihood for spatial point patterns: (with discussion). Australian & New Zealand Journal of Statistics, 42, 283–322.
    Paper not yet in RePEc: Add citation now
  4. Baddeley, A., Coeurjolly, J.‐F., Rubak, E., & Waagepetersen, R. (2014). Logistic regression for spatial Gibbs point processes. Biometrika, 101, 377–392.

  5. Baddeley, A., Rubak, E., & Turner, R. (2015). Spatial point patterns: Methodology and applications with R. Chapman and Hall/CRC Press.
    Paper not yet in RePEc: Add citation now
  6. Berk, R., Brown, L., Buja, A., Zhang, K., & Zhao, L. (2013). Valid post‐selection inference. The Annals of Statistics, 41, 802–837.
    Paper not yet in RePEc: Add citation now
  7. Besag, J. (1978). Some methods of statistical analysis for spatial data. Bulletin International Statistical Institute, 47, 77–92.
    Paper not yet in RePEc: Add citation now
  8. Billiot, J.‐M., Coeurjolly, J.‐F., & Drouilhet, R. (2008). Maximum pseudolikelihood estimator for exponential family models of marked Gibbs point processes. Electronic Journal of Statistics, 2, 234–264.
    Paper not yet in RePEc: Add citation now
  9. Breheny, P., & Huang, J. (2011). Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection. The Annals of Applied Statistics, 5, 232.
    Paper not yet in RePEc: Add citation now
  10. Choiruddin, A., Coeurjolly, J.‐F., & Letué, F. (2018). Convex and non‐convex regularization methods for spatial point processes intensity estimation. Electronic Journal of Statistics, 12, 1210–1255.
    Paper not yet in RePEc: Add citation now
  11. Choiruddin, A., Coeurjolly, J.‐F., & Waagepetersen, R. (2021). Information criteria for inhomogeneous spatial point processes. Australian & New Zealand Journal of Statistics, 63, 119–143.
    Paper not yet in RePEc: Add citation now
  12. Coeurjolly, J.‐F. (2015). Almost sure behavior of functionals of stationary Gibbs point processes. Statistics & Probability Letters, 97, 241–246.
    Paper not yet in RePEc: Add citation now
  13. Coeurjolly, J.‐F., & Drouilhet, R. (2010). Asymptotic properties of the maximum pseudo‐likelihood estimator for stationary Gibbs point processes including the Lennard‐Jones model. Electronic Journal of Statistics, 4, 677–706.
    Paper not yet in RePEc: Add citation now
  14. Coeurjolly, J.‐F., & Lavancier, F. (2017). Parametric estimation of pairwise Gibbs point processes with infinite range interaction. Bernoulli, 23, 1299–1334.
    Paper not yet in RePEc: Add citation now
  15. Coeurjolly, J.‐F., & Rubak, E. (2013). Fast covariance estimation for innovations computed from a spatial Gibbs point process. Scandinavian Journal of Statistics, 40, 669–684.

  16. Coeurjolly, J.‐F., Møller, J., & Waagepetersen, R. (2017). A tutorial on palm distributions for spatial point processes. International Statistical Review, 85, 404–420.

  17. Condit, R. (1998). Tropical forest census plots: Methods and results from Barro Colorado Island, Panama and a comparison with other plots. Springer Science & Business Media.
    Paper not yet in RePEc: Add citation now
  18. Daley, D. J., & Vere‐Jones, D. (2007). An introduction to the theory of point processes: Volume II: General theory and structure. Springer Science & Business Media.
    Paper not yet in RePEc: Add citation now
  19. Daniel, J., Horrocks, J., & Umphrey, G. J. (2018). Penalized composite likelihoods for inhomogeneous Gibbs point process models. Computational Statistics & Data Analysis, 124, 104–116.

  20. Dereudre, D., & Lavancier, F. (2009). Campbell equilibrium equation and pseudo‐likelihood estimation for non‐hereditary Gibbs point processes. Bernoulli, 15, 1368–1396.
    Paper not yet in RePEc: Add citation now
  21. Dereudre, D., & Lavancier, F. (2017). Consistency of likelihood estimation for Gibbs point processes. The Annals of Statistics, 45, 744–770.
    Paper not yet in RePEc: Add citation now
  22. Dereudre, D., Drouilhet, R., & Georgii, H.‐O. (2012). Existence of Gibbsian point processes with geometry‐dependent interactions. Probability Theory and Related Fields, 153, 643–670.
    Paper not yet in RePEc: Add citation now
  23. Fan, J., & Li, R. (2001). Variable selection via nonconcave penalized likelihood and its oracle properties. Journal of the American Statistical Association, 96, 1348–1360.

  24. Fan, J., & Peng, H. (2004). Nonconcave penalized likelihood with a diverging number of parameters. The Annals of Statistics, 32, 928–961.
    Paper not yet in RePEc: Add citation now
  25. Friedman, J., Hastie, T., & Tibshirani, R. (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33, 1.

  26. Friedman, J., Hastie, T., Höfling, H., & Tibshirani, R. (2007). Pathwise coordinate optimization. The Annals of Applied Statistics, 1, 302–332.
    Paper not yet in RePEc: Add citation now
  27. Gao, X., & Song, P. X.‐K. (2010). Composite likelihood bayesian information criteria for model selection in high‐dimensional data. Journal of the American Statistical Association, 105, 1531–1540.

  28. Georgii, H.‐O. (1979). Canonical Gibbs measures, volume 760 of lecture notes in mathematics.
    Paper not yet in RePEc: Add citation now
  29. Georgii, H.‐O. (2011). Gibbs measures and phase transitions (Vol. 9). Walter de Gruyter.
    Paper not yet in RePEc: Add citation now
  30. Guan, Y., & Shen, Y. (2010). A weighted estimating equation approach for inhomogeneous spatial point processes. Biometrika, 97, 867–880.

  31. Hengl, T., Sierdsema, H., Radović, A., & Dilo, A. (2009). Spatial prediction of species' distributions from occurrence‐only records: Combining point pattern analysis, ENFA and regression‐kriging. Ecological Modelling, 220, 3499–3511.

  32. Hoerl, A., & Kennard, R. (1988). Ridge regression. In Encyclopedia of Statistical Sciences? (Vol. 8). https://doi.org/10.1002/0471667196.ess2280.pub2.
    Paper not yet in RePEc: Add citation now
  33. Hubbell, S. P., Condit, R. & Foster, R. B. (2005). Barro Colorado forest census plot data.
    Paper not yet in RePEc: Add citation now
  34. Hubbell, S. P., Foster, R. B., O'Brien, S. T., Harms, K. E., Condit, R., Wechsler, B., Wright, S. J., & De Lao, S. L. (1999). Light‐gap disturbances, recruitment limitation, and tree diversity in a neotropical forest. Science, 283, 554–557.
    Paper not yet in RePEc: Add citation now
  35. Hui, F. K., Warton, D. I., & Foster, S. D. (2015). Tuning parameter selection for the adaptive lasso using Eric. Journal of the American Statistical Association, 110, 262–269.

  36. Illian, J., Penttinen, A., Stoyan, H., & Stoyan, D. (2008). Statistical analysis and modelling of spatial point patterns (Vol. 70). John Wiley & Sons.
    Paper not yet in RePEc: Add citation now
  37. Ivanoff, S., Picard, F., & Rivoirard, V. (2016). Adaptive Lasso and group‐Lasso for functional Poisson regression. The Journal of Machine Learning Research, 17, 1903–1948.
    Paper not yet in RePEc: Add citation now
  38. Jensen, E. B. V., & Nielsen, L. S. (2001). A review on inhomogeneous Markov point processes. Lecture Notes‐Monograph Series, 37, 297–318.
    Paper not yet in RePEc: Add citation now
  39. Jensen, J. L., & Künsch, H. R. (1994). On asymptotic normality of pseudo likelihood estimates for pairwise interaction processes. Annals of the Institute of Statistical Mathematics, 46, 475–486.

  40. Jensen, J. L., & Møller, J. (1991). Pseudolikelihood for exponential family models of spatial point processes. The Annals of Applied Probability, 1, 445–461.
    Paper not yet in RePEc: Add citation now
  41. Lee, J. D., Sun, D. L., Sun, Y., & Taylor, J. E. (2016). Exact post‐selection inference, with application to the lasso. The Annals of Statistics, 44, 907–927.
    Paper not yet in RePEc: Add citation now
  42. Mase, S. (1995). Consistency of the maximum pseudo‐likelihood estimator of continuous state space Gibbsian processes. The Annals of Applied Probability, 5, 603–612.
    Paper not yet in RePEc: Add citation now
  43. Møller, J., & Waagepetersen, R. P. (2003). Statistical inference and simulation for spatial point processes. Chapman and Hall/CRC Press.
    Paper not yet in RePEc: Add citation now
  44. Møller, J., & Waagepetersen, R. P. (2007). Modern statistics for spatial point processes. Scandinavian Journal of Statistics, 34, 643–684.

  45. Rajala, T., Murrell, D., & Olhede, S. (2018). Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection. Journal of the Royal Statistical Society Series C, 67, 1237–1273.

  46. Reynaud‐Bouret, P. (2003). Adaptive estimation of the intensity of inhomogeneous Poisson processes via concentration inequalities. Probability Theory and Related Fields, 126, 103–153.
    Paper not yet in RePEc: Add citation now
  47. Ripley, B. D. (1991). Statistical inference for spatial processes. Cambridge University Press.
    Paper not yet in RePEc: Add citation now
  48. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.
    Paper not yet in RePEc: Add citation now
  49. Stein, M. L. (1999). Interpolation of spatial data: Some theory for kriging Springer Series in Statistics (1st ed.). Springer‐Verlag. http://gen.lib.rus.ec/book/index.php?md5=e2da912dee4e6b700d99ddb258ef8d4a.
    Paper not yet in RePEc: Add citation now
  50. Taylor, J., & Tibshirani, R. (2018). Post‐selection inference for‐penalized likelihood models. Canadian Journal of Statistics, 46, 41–61.
    Paper not yet in RePEc: Add citation now
  51. Team, R. C. (2019). R: A language and environment for statistical computing, version 3.3. 1. R Foundation for Statistical Computing.
    Paper not yet in RePEc: Add citation now
  52. Thurman, A. L., & Zhu, J. (2014). Variable selection for spatial Poisson point processes via a regularization method. Statistical Methodology, 17, 113–125.
    Paper not yet in RePEc: Add citation now
  53. Thurman, A. L., Fu, R., Guan, Y., & Zhu, J. (2015). Regularized estimating equations for model selection of clustered spatial point processes. Statistica Sinica, 25, 173–188.
    Paper not yet in RePEc: Add citation now
  54. Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological), 58, 267–288.
    Paper not yet in RePEc: Add citation now
  55. Vasseur, T., Coeurjolly, J.‐F. and Dereudre, D. (2020). Existence of inhomogeneous Gibb point processes in the infinite volume. Preprint.
    Paper not yet in RePEc: Add citation now
  56. Waagepetersen, R. P. (2007). An estimating function approach to inference for inhomogeneous Neyman–Scott processes. Biometrics, 63, 252–258.

  57. Xanh, N. X., & Zessin, H. (1979). Integral and differential characterizations of the Gibbs process. Mathematische Nachrichten, 88, 105–115.
    Paper not yet in RePEc: Add citation now
  58. Yue, Y., & Loh, J. M. (2015). Variable selection for inhomogeneous spatial point process models. Canadian Journal of Statistics, 43, 288–305.
    Paper not yet in RePEc: Add citation now
  59. Zhang, C.‐H. (2010). Nearly unbiased variable selection under minimax concave penalty. The Annals of Statistics, 38, 894–942.
    Paper not yet in RePEc: Add citation now
  60. Zou, H. (2006). The adaptive lasso and its oracle properties. Journal of the American Statistical Association, 101, 1418–1429.

  61. Zou, H., & Zhang, H. H. (2009). On the adaptive elastic‐net with a diverging number of parameters. The Annals of Statistics, 37, 1733.
    Paper not yet in RePEc: Add citation now
  62. Zou, H., Hastie, T., & Tibshirani, R. (2007). On the Degrees of freedom of the Lasso. The Annals of Statistics, 35, 2173–2192.
    Paper not yet in RePEc: Add citation now

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    RePEc:eee:csdana:v:54:y:2010:i:10:p:2230-2243.

    Full description at Econpapers || Download paper

  46. .

    Full description at Econpapers || Download paper

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    RePEc:wii:wpaper:55.

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  48. Penalized factor mixture analysis for variable selection in clustered data. (2009). Galimberti, Giuliano ; Viroli, Cinzia ; Montanari, Angela.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:53:y:2009:i:12:p:4301-4310.

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  49. Confidence sets based on penalized maximum likelihood estimators. (2008). Schneider, Ulrike ; Pötscher, Benedikt ; Potscher, Benedikt M..
    In: MPRA Paper.
    RePEc:pra:mprapa:9062.

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  50. Challenges and opportunities in high-dimensional choice data analyses. (2008). Kreulen, Jeffrey ; Bradlow, Eric ; Madigan, David ; Bodapati, Anand ; Montgomery, Alan ; Kamakura, Wagner ; Naik, Prasad ; Lenk, Peter ; Wedel, Michel ; Bacon, Lynd .
    In: Marketing Letters.
    RePEc:kap:mktlet:v:19:y:2008:i:3:p:201-213.

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  51. Catching Growth Determinants with the Adaptive LASSO. (2008). Wagner, Martin ; Schneider, Ulrike.
    In: Economics Series.
    RePEc:ihs:ihsesp:232.

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  52. Subset selection for vector autoregressive processes using Lasso. (2008). Chang, Ya-Mei ; Hsu, Nan-Jung ; Hung, Hung-Lin.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:52:y:2008:i:7:p:3645-3657.

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  53. Regularized simultaneous model selection in multiple quantiles regression. (2008). Yuan, Ming ; Zou, Hui.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:52:y:2008:i:12:p:5296-5304.

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  54. A note on adaptive group lasso. (2008). Wang, Hansheng ; Leng, Chenlei.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:52:y:2008:i:12:p:5277-5286.

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  55. On the distribution of the adaptive LASSO estimator. (2007). Schneider, Ulrike ; Pötscher, Benedikt ; Potscher, Benedikt M..
    In: MPRA Paper.
    RePEc:pra:mprapa:6913.

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  56. Confidence Sets Based on Sparse Estimators Are Necessarily Large. (2007). Pötscher, Benedikt ; Potscher, Benedikt M..
    In: MPRA Paper.
    RePEc:pra:mprapa:5677.

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  57. On the distribution of penalized maximum likelihood estimators: The LASSO, SCAD, and thresholding.. (2007). Pötscher, Benedikt ; Leeb, Hannes ; Potscher, Benedikt M..
    In: MPRA Paper.
    RePEc:pra:mprapa:5615.

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  58. Efficient algorithms for computing the best subset regression models for large-scale problems. (2007). Kontoghiorghes, Erricos ; Hofmann, Marc ; Gatu, Cristian .
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:52:y:2007:i:1:p:16-29.

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  59. Sparse Estimators and the Oracle Property, or the Return of Hodges Estimator. (2007). Pötscher, Benedikt ; Leeb, Hannes.
    In: Cowles Foundation Discussion Papers.
    RePEc:cwl:cwldpp:1500.

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  60. Regularization in statistics. (2006). Tsybakov, Alexandre ; Li, Bo ; Fan, Jianqing ; Rivero, Carlos ; Yu, Bin ; Vaart, Aad ; Valdes, Teofilo ; Geer, Sara ; Bickel, Peter.
    In: TEST: An Official Journal of the Spanish Society of Statistics and Operations Research.
    RePEc:spr:testjl:v:15:y:2006:i:2:p:271-344.

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