Semiparametric Statistical Methods for Replicated Point Processes

Funded by the US National Science Foundation, grant DMS 1505780, Aug 2015 – July 2019


Project Summary

The main goal of this project is the development of statistical tools for the analysis of points that occur at random in time or space, such as the locations of street robberies in a given city or the timings of spikes of neural activity for an individual performing a certain task.
This type of data arises in many different fields, like neuroscience, ecology, finance, astronomy, seismology, criminology, and many others. The statistical methods to be developed under this project will then provide new data-analysis and inference tools for researchers and practitioners in diverse scientific fields.
In this project we will develop semiparametric methods for estimation of the intensity functions of spatial and temporal replicated point processes. These have become increasingly common in recent years, and the possibility of pooling data across replications allows for the development of more efficient statistical methods.

Acknowledgement and Disclaimer

This material is based upon work supported by the National Science Foundation under Grant Number 1505780. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


Computer programs (Matlab)

Joint models for grid point and response processes in longitudinal and functional data

The zip file COVMKPP_package contains Matlab programs for estimation of the covariation models proposed by Gervini and Baur (2020).

Doubly stochastic models for spatio-temporal covariation of replicated point processes

The zip file STPP_package contains Matlab programs for estimation of the models proposed by Gervini (2021). A brief tutorial is included.

Exploring patterns of demand in bike sharing systems

The zip file Bike_programs contains Matlab programs used in Gervini and Khanal (2019).

Multiplicative Component models for replicated point processes

The zip files Temporal_MCA_package and Spatial_MCA_package contain Matlab programs for fitting temporal and spatial Multiplicative Component models of Gervini (2017). Tutorials explaining how to use the programs are included.

Independent Component models for replicated point processes

The zip files Temporal_ICAPP_package and Spatial_ICAPP_package contain Matlab programs for fitting the temporal and spatial Independent Component models of Gervini (2016). They also include tutorials explaining how to use the programs.


Last updated: 30 Jun 2021, 21:30 hs