A fast spectral quasi-likelihood approach for spatial point processes

C. Deng, R. P. Waagepetersen, M. Wang, Y. Guan

Research output: Contribution to journalArticlepeer-review


In applications of spatial point processes, it is often of interest to fit a parametric model for the intensity function. For this purpose Guan et al. (2015) recently introduced a quasi-likelihood type estimating function that is optimal in a certain class of first-order estimating functions. However, depending on the choice of certain tuning parameters, the implementation suggested in Guan et al. (2015) can be very demanding both in terms of computing time and memory requirements. Using a novel spectral representation, we construct in this paper an implementation that is computationally much more efficient than the one proposed in Guan et al. (2015).

Original languageEnglish (US)
Pages (from-to)59-64
Number of pages6
JournalStatistics and Probability Letters
StatePublished - Feb 2018


  • Estimating function
  • Quasi-Likelihood
  • Spatial point process
  • Spectral approach

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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