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.

Altieri, L., Farcomeni, A., Fegatelli, D.a. (2023). Continuous time-interaction processes for population size estimation, with an application to drug dealing in Italy. BIOMETRICS, 79(2), 1254-1267 [10.1111/biom.13662].

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

Farcomeni, Alessio;
2023-06-01

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.
giu-2023
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-S/01 - STATISTICA
English
Hawkes processes
capture-recapture
conditional likelihood
drug-dealing data
self-correcting processes
time-interaction processes
Altieri, L., Farcomeni, A., Fegatelli, D.a. (2023). Continuous time-interaction processes for population size estimation, with an application to drug dealing in Italy. BIOMETRICS, 79(2), 1254-1267 [10.1111/biom.13662].
Altieri, L; Farcomeni, A; Fegatelli, Da
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/326903
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