Results 1 to 10 of about 6,905,405 (185)
Quasi-likelihood for Spatial Point Processes. [PDF]
J R Stat Soc Series B Stat Methodol, 2015 Fitting regression models for intensity functions of spatial point processes is of great interest in ecological and epidemiological studies of association between spatially referenced events and geographical or environmental covariates.
Guan Y, Jalilian A, Waagepetersen R.
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Deconvolution of calcium imaging data using marked point processes. [PDF]
PLoS Comput Biol, 2020 Calcium imaging has been widely used for measuring spiking activities of neurons. When using calcium imaging, we need to extract summarized information from the raw movie beforehand.
Shibue R, Komaki F.
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Point Processes in a Metric Space and Their Applications
Mathematics, 2022 Point processes are important in extreme value theory due to their equivalent formulations of two popular models in various applications: the block maxima models and the peak-over-threshold model.
Yuwei Zhao
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Rain process models and convergence to point processes [PDF]
Nonlinear Processes in Geophysics, 2023 A variety of stochastic models have been used to describe time series of precipitation or rainfall. Since many of these stochastic models are simplistic, it is desirable to develop connections between the stochastic models and the underlying physics of ...
S. Hottovy, S. N. Stechmann
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Further results on why a point process is effective for estimating correlation between brain regions
Papers in Physics, 2020 Signals from brain functional magnetic resonance imaging (fMRI) can be efficiently represented by a sparse spatiotemporal point process, according to a recently introduced heuristic signal processing scheme.
I. Cifre +4 more
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Exponential Inequality of Marked Point Processes
Mathematics, 2023 This paper presents the uniform concentration inequality for the stochastic integral of marked point processes. We developed a new chaining method to obtain the results.
Chen Li, Yuping Song
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Revealing Spectrum Features of Stochastic Neuron Spike Trains
Mathematics, 2020 Power spectra of spike trains reveal important properties of neuronal behavior. They exhibit several peaks, whose shape and position depend on applied stimuli and intrinsic biophysical properties, such as input current density and channel noise.
Simone Orcioni +3 more
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DECOMPOSING IMAGES INTO TRIANGLES BY DELAUNAY POINT PROCESSES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 We propose a method for decomposing images into triangles. Contrary to superpixel methods, our output representation both preserves the geometric information disseminated in input images, and has an attractive storage capacity.
D. Chai
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Rank-Based Mixture Models for Temporal Point Processes
Frontiers in Applied Mathematics and Statistics, 2022 Temporal point process, an important area in stochastic process, has been extensively studied in both theory and applications. The classical theory on point process focuses on time-based framework, where a conditional intensity function at each given ...
Yang Chen, Yijia Ma, Wei Wu
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Axioms, 2020 A plethora of applications from mathematical programming, such as minimax, and mathematical programming, penalization, fixed point to mention a few can be framed as equilibrium problems.
Nopparat Wairojjana +3 more
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