Exact Bayesian Inference for Level-Set Cox Processes with Piecewise Constant Intensity Function | PERPUSTAKAAN UNIVERSITAS KATOLIK PARAHYANGAN

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Exact Bayesian Inference for Level-Set Cox Processes with Piecewise Constant Intensity Function

Goncalves, Flavio B. - Nama Orang; Dias, Barbara C. C. - Nama Orang;

This article proposes a new methodology to perform Bayesian inference for a class of multidimensional Cox processes in which the intensity function is piecewise constant. Poisson processes with piecewise constant intensity functions are believed to be suitable to model a variety of point process phenomena and, given its simpler structure, are expected to provide more precise inference when compared to processes with nonparametric and continuously varying intensity functions. The partition of the space domain is flexibly determined by a level-set function of a latent Gaussian process. Despite the intractability of the likelihood function and the infinite dimensionality of the parameter space, inference is performed exactly, in the sense that no space discretization approximation is used and MCMC error is the only source of inaccuracy. That is achieved by using retrospective sampling techniques and devising a pseudo-marginal infinite-dimensional MCMC algorithm that converges to the exact target posterior distribution. Computational efficiency is favored by considering a nearest neighbor Gaussian process, allowing for the analysis of large datasets. An extension to consider spatiotemporal models is also proposed. The efficiency of the proposed methodology is investigated in simulated examples and its applicability is illustrated in the analysis of some real point process datasets.

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Barcode		Tipe Koleksi	Nomor Panggil	Lokasi	Status
art144985	null	Artikel		Gdg9-Lt3	Tersedia namun tidak untuk dipinjamkan - No Loan

Informasi Detail

Judul Seri: JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS; Vol.32 No.1 March 2023
No. Panggil: -
Penerbit: : .,
Deskripsi Fisik: p. 1-18
Bahasa: English
ISBN/ISSN: -
Klasifikasi: NONE
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: -
Subjek: GAUSSIAN PROCESS
POISSON ESTIMATOR
PSEUDO-MARGINAL MCMC
NNGP
PSEUDO ESTIMATOR
RETROSPECTIVE SAMPLING
Info Detail Spesifik: https://doi.org/10.1080/10618600.2022.2092117
Pernyataan Tanggungjawab: Flavio B. Goncalves, Barbara C. C. Dias

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