In this paper, we exploit some theoretical results, from which we know the expected value of the K-function weighted by the true first-order intensity function of a point pattern. This theoretical result can serve as an estimation method for obtaining the parameter estimates of a specific model, assumed for the data. The only requirement is the knowledge of the first-order intensity function expression, completely avoiding writing the likelihood, which is often complex to deal with in point process models. We illustrate the method through simulation studies for spatio-temporal point processes.

Nicoletta D'Angelo, Giada Adelfio (2023). Minimum contrast for point processes' first-order intensity estimation. In Book of Short Papers.

Minimum contrast for point processes' first-order intensity estimation

Nicoletta D'Angelo
;
Giada Adelfio
2023-01-01

Abstract

In this paper, we exploit some theoretical results, from which we know the expected value of the K-function weighted by the true first-order intensity function of a point pattern. This theoretical result can serve as an estimation method for obtaining the parameter estimates of a specific model, assumed for the data. The only requirement is the knowledge of the first-order intensity function expression, completely avoiding writing the likelihood, which is often complex to deal with in point process models. We illustrate the method through simulation studies for spatio-temporal point processes.
2023
9788891935618
Nicoletta D'Angelo, Giada Adelfio (2023). Minimum contrast for point processes' first-order intensity estimation. In Book of Short Papers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/590773
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