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[PDF] Top 20 Takacs-Fiksel method for stationary marked Gibbs point processes

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Takacs-Fiksel method for stationary marked Gibbs point processes

Takacs-Fiksel method for stationary marked Gibbs point processes

... i.e. for a large class of stationary marked Gibbs models and test ...The method employed to prove asymptotic normality is based on a conditional centering assumption, first appeared in ... Voir le document complet

27

Residuals and goodness-of-fit tests for stationary marked Gibbs point processes

Residuals and goodness-of-fit tests for stationary marked Gibbs point processes

... data. For spatial point processes, the concept of residuals has been recently proposed by Baddeley et ...equation for marked Gibbs point ...on stationary ... Voir le document complet

41

Towards optimal Takacs–Fiksel estimation

Towards optimal Takacs–Fiksel estimation

... obtain Takacs- Fiksel estimates and usually weight functions are chosen by ad hoc reasoning pay- ing attention to ease of implementation or to handle patterns which are sampled in situ, like in Tomppo ... Voir le document complet

23

Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits

Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits

... Cao et al. ( 2019 )) have achieved O( p Υ T AT ln(T )) regret, when Υ T is known. CUSUM-UCB is based on a variant of a two-sided CUSUM test, that uses the first M samples from one arm to compute an initial average, and ... Voir le document complet

17

ALE Methods for Determining Stationary Solutions Metal Forming Processes

ALE Methods for Determining Stationary Solutions Metal Forming Processes

... Actually, the steady state is reached rather quickly after a 15 degrees rotation. Its obtained after about 440 time steps. The Godunov-like algorithm is approximately 30% faster than the SUPG method (4 min 40 s ... Voir le document complet

10

Moment formulae for general point processes

Moment formulae for general point processes

... Introduction Point processes constitute a general framework used to model a wide variety of ...Poisson point process, which is one of the reasons for its use in a lot of practical ...tools ... Voir le document complet

17

Zeros of smooth stationary Gaussian processes

Zeros of smooth stationary Gaussian processes

... R Card(Z ∩ [0, R]), that is concentration around the mean at exponential speed in R. Their proof relies on the existence of an analytic extension of f to horizontal strips in the complex plane. Note that the ... Voir le document complet

74

SPADE: A Small Particle Detection Method Using A Dictionary Of Shapes Within The Marked Point Process Framework

SPADE: A Small Particle Detection Method Using A Dictionary Of Shapes Within The Marked Point Process Framework

... methods for similar tasks in terms of detection quality, although it was computationally more ...the marked point pro- cesses framework to objects only a few pixels ... Voir le document complet

2

Recursion on the marginals and normalizing constant for Gibbs processes - Version 2

Recursion on the marginals and normalizing constant for Gibbs processes - Version 2

... see for example Moeller et al. (2006) for efficient Monte Carlo ...see for example Liu (2001); of course this is an interesting preliminary for further statistical procedures such as sim- ... Voir le document complet

15

LIDAR WAVEFORM MODELING USING A MARKED POINT PROCESS

LIDAR WAVEFORM MODELING USING A MARKED POINT PROCESS

... Index Terms— Signal reconstruction, Lidar, Source modeling, Marked point process, RJMCMC, 3D point cloud. 1. INTRODUCTION Airborne laser scanning is an active remote sensing technique pro- viding ... Voir le document complet

5

An Unsupervised Retinal Vessel Extraction and Segmentation Method Based On a Tube Marked Point Process Model

An Unsupervised Retinal Vessel Extraction and Segmentation Method Based On a Tube Marked Point Process Model

... A point process on S is a set of points {S1, S2, ...ith point. In a connected- tube marked point process, each point Si is associated with a tube mark, which consists of random ... Voir le document complet

6

Gibbs point field models for extraction problems in image analysis

Gibbs point field models for extraction problems in image analysis

... that, for a given problem, there exists a Gibbs field such that its ground states represent regularized solutions of the ...the Gibbs random fields approach, the choice of an energy function ... Voir le document complet

7

SPADE: A Small Particle Detection Method Using A Dictionary Of Shapes Within The Marked Point Process Framework

SPADE: A Small Particle Detection Method Using A Dictionary Of Shapes Within The Marked Point Process Framework

... † Inria ¶ Centre National de la Recherche Scientifique § Valrose Biology Institute ABSTRACT We introduce SPADE (small particle detection), a novel method to detect and characterize objects only a few pixel large ... Voir le document complet

2

Characterising the nonequilibrium stationary states of Ornstein-Uhlenbeck processes Nonequilibrium stationary states of Ornstein-Uhlenbeck processes

Characterising the nonequilibrium stationary states of Ornstein-Uhlenbeck processes Nonequilibrium stationary states of Ornstein-Uhlenbeck processes

... Ornstein-Uhlenbeck process is reversible and obeys detailed balance with respect to the above distribution. The Einstein relation σ 2 = kT γ is an example of an equilibrium fluctuation-dissipation relation. Generalising ... Voir le document complet

41

Random discretization of stationary continuous time processes

Random discretization of stationary continuous time processes

... In Section 3, we present the more specific situation of a regularly varying covariance where preservation or non-preservation of the memory can be quantified. In particular, we prove that for heavy tailed sampling ... Voir le document complet

18

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes

... 7. Conclusion In this paper we proposed a method allowing one to make finite-sample inference on the parameters of autoregressive models. This was made possible by special properties of Markov processes. ... Voir le document complet

43

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes

... The intercalary independence property was apparently first given without proof by Ogawara 1951 for univariate Markov processes, while the truncation property was used implicitly by him a[r] ... Voir le document complet

43

Exponential convergence to quasi-stationary distribution for multi-dimensional diffusion processes

Exponential convergence to quasi-stationary distribution for multi-dimensional diffusion processes

... eigenmeasure for the adjoint generator is given by the quasi-stationary distribution α [19] and an eigenfunction for the generator by [4, Proposition ...(2.1) for some t > ... Voir le document complet

24

Smaller population size at the MRCA time for stationary branching processes

Smaller population size at the MRCA time for stationary branching processes

... description of the genealogy in the critical and sub-critical cases. See the approach of Abra- ham and Delmas [1] (2008) or Berestycki, Kyprianou and Murillo [7] (2009) for a description of the genealogy in the ... Voir le document complet

28

Geometric Feature Extraction by a Multi-Marked Point Process

Geometric Feature Extraction by a Multi-Marked Point Process

... see for example on the crack image where many small lines have been ...interesting point consists in comparing both the models on textures composed of a foreground layer and a homogeneous ...satisfactory ... Voir le document complet

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