Continuous time‐interaction processes for population size estimation, with an application to drug dealing in Italy

Linda Altieri, Alessio Farcomeni and Danilo Alunni Fegatelli

Biometrics, 2023, vol. 79, issue 2, 1254-1267

Abstract: We introduce a time‐interaction point process where the occurrence of an event can increase (self‐excitement) or reduce (self‐correction) the probability of future events. Self‐excitement and self‐correction are allowed to be triggered by the same event, at different timescales; other effects such as those of covariates, unobserved heterogeneity, and temporal dependence are also allowed in the model. We focus on capture‐recapture data, as our work is motivated by an original example about the estimation of the total number of drug dealers in Italy. To do so, we derive a conditional likelihood formulation where only subjects with at least one capture are involved in the inference process. The result is a novel and flexible continuous‐time population size estimator. A simulation study and the analysis of our motivating example illustrate the validity of our approach in several scenarios.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/biom.13662

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:79:y:2023:i:2:p:1254-1267

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0006-341X

Access Statistics for this article

More articles in Biometrics from The International Biometric Society
Bibliographic data for series maintained by Wiley Content Delivery ().