Results 31 to 40 of about 3,602,130 (312)

Insertion and deletion tolerance of point processes [PDF]

open access: yes, 2013
We develop a theory of insertion and deletion tolerance for point processes. A process is insertion-tolerant if adding a suitably chosen random point results in a point process that is absolutely continuous in law with respect to the original process ...
Holroyd, Alexander E.   +3 more
core   +1 more source

Determinanti geografiche della mortalità per tumore tiroideo nella Sicilia orientale

open access: yesBollettino della Società Geografica Italiana, 2022
The study of geographic determinants in the processes of spreading infectious diseases has a long tradition. As a result of the increase in the incidence of chronic and non-infectious diseases, such as cancer and various types of heart disease ...
Francesca Bitonti, Angelo Mazza
doaj   +1 more source

Optimizing carbon reduction strategies in Trinidad and Tobago’s power generation sector: insights from carbon emission pinch analysis

open access: yesCarbon Management
This study examines Trinidad and Tobago’s (T&T) efforts to expand energy capacity while reducing power-sector greenhouse gas (GHG) emissions from 2006 to 2030. Using a carbon-constrained energy planning (CCEP) framework and carbon emission pinch analysis
Dillon Ramsook   +2 more
doaj   +1 more source

A Simultaneous Estimation of the Baseline Intensity and Parameters for Modulated Renewal Processes

open access: yesAxioms, 2022
This paper proposes a semiparametric solution to estimate the intensity (hazard) function of modulated renewal processes: a nonparametric estimate for the baseline intensity function together with a parametric estimate of the model parameters of the ...
Jiancang Zhuang, Hai-Yen Siew
doaj   +1 more source

Distinguishing Synchronous and Time Varying Synergies using Point Process Interval Statistics: Motor Primitives in Frog and Rat.

open access: yesFrontiers in Computational Neuroscience, 2013
We present and apply a method that uses point process statistics to discriminate the forms of synergies in motor pattern data, prior to explicit synergy extraction. The method uses electromyogram (EMG) pulse peak timing or onset timing.
Corey B Hart   +3 more
doaj   +1 more source

Cox Processes Associated with Spatial Copula Observed through Stratified Sampling

open access: yesMathematics, 2021
Cox processes, also called doubly stochastic Poisson processes, are used for describing phenomena for which overdispersion exists, as well as Poisson properties conditional on environmental effects.
Walguen Oscar, Jean Vaillant
doaj   +1 more source

Video Sensor-Based Complex Scene Analysis with Granger Causality

open access: yesSensors, 2013
In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes.
Shuang Wu   +4 more
doaj   +1 more source

Integration with Stochastic Point Processes [PDF]

open access: yesACM Transactions on Graphics, 2016
We present a novel comprehensive approach for studying error in integral estimation with point distributions based on point process statistics. We derive exact formulae for bias and variance of integral estimates in terms of the spatial or spectral characteristics of integrands and first- and-second order product density measures of general point ...
openaire   +2 more sources

Determinantal Point Processes for Coresets

open access: yesJ. Mach. Learn. Res., 2018
When faced with a data set too large to be processed all at once, an obvious solution is to retain only part of it. In practice this takes a wide variety of different forms, and among them "coresets" are especially appealing. A coreset is a (small) weighted sample of the original data that comes with the following guarantee: a cost function can be ...
Tremblay, Nicolas   +2 more
openaire   +4 more sources

Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities [PDF]

open access: yes, 2009
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian process is a useful way to place a prior distribution on this intensity.
Murray, Iain   +6 more
core   +1 more source

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