[PDF] Top 20 Determinantal point process models and statistical inference : Extended version
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Determinantal point process models and statistical inference : Extended version
... physical process generating a spatial point process ...DPP models is to provide empirical models with a parsimonious parametrization, where we can compare different spatial point ... Voir le document complet
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Adaptive estimating function inference for non-stationary determinantal point processes
... ] and [ 4 ] usually compare results for several values of R corresponding to different multiples of some parameter associated with ‘range of corre- ...cluster process this parameter could ...a ... Voir le document complet
36
ESTIMATION OF THE DENSITY OF A DETERMINANTAL PROCESS
... starting point of this work goes back to 2007 when Persi Diaconis visited our Laboratory Jean-Alexandre Dieudonné in ...that determinantal processes were emerging in many areas and that there was no ... Voir le document complet
25
Standard and robust intensity parameter estimation for stationary determinantal point processes
... Repulsive point processes; Statistical inference; Robust statistics; Sample quantiles; Brillinger ...Spatial point patterns are datasets containing the random locations of some event of ... Voir le document complet
22
Contrast estimation for parametric stationary determinantal point processes
... tal point processes. These processes form a useful class of models for repulsive (or regular, or inhibitive) point patterns and are already applied in numerous statistical ... Voir le document complet
30
Statistical inference in compound functional models
... (25) and (26) we get the result. 5. Discussion and outlook We presented a new framework, called the compound functional model, for performing various statistical tasks such as prediction, estimation ... Voir le document complet
17
Quantifying repulsiveness of determinantal point processes
... Abstract Determinantal point processes (DPPs) have recently proved to be a useful class of models in several areas of statistics, including spatial statistics, statistical learning and ... Voir le document complet
31
Perfect Simulation of Determinantal Point Processes
... on determinantal point pro- cesses and we provide a lower and a upper bound for the coalescence time in general ...notation and recall the definition of a point process, ... Voir le document complet
16
On a few statistical applications of determinantal point processes
... min and r max are user-specified ...0.01 and r max as one quarter of the side length of the observation ...β and θ can be found in [ 5 ], in the particular case of stationary ...the point ... Voir le document complet
24
Brillinger mixing of determinantal point processes and statistical applications
... Introduction Determinantal point processes (DPPs) are models for repulsive point patterns, where nearby points of the process tend to repel each ...[23] and extensively studied ... Voir le document complet
25
Statistical inference for epidemic models approximated by diffusion processes
... Inference for discrete observations of diusion or Gaussian processes with small diusion coe cient Epidemics incompletely observed: partially and integrated diusion processes (Work in progress) Gaussian ... Voir le document complet
34
Empirical Projected Copula Process and Conditional Independence An Extended Version
... Empirical Process, Weak convergence, Copula ...copula process and explain its importance in non parametric conditional indepen- dence ...in statistical theory was first adressed in the paper ... Voir le document complet
21
Termination of Priority Rewriting - Extended version
... narrowing process only depends on the term to be rewritten and of the rule considered, simu- lating IP -rewriting of ground instances of a term with a given rule requires to take into account the narrowing ... Voir le document complet
23
Identification, Weak Instruments and Statistical Inference in Econometrics
... tests and confidence ...reliable inference procedures in ...specialized, and in another way, more general — and ...general statistical issues raised by identification in econometric ... Voir le document complet
44
Identification, Weak Instruments and Statistical Inference in Econometrics
... building models, and assessing alternative ...new models: multivariate time series models, GARCH-types processes; (3) a greater ability to estimate nonlinear models which require an ... Voir le document complet
45
Statistical Inference for Oscillation Processes
... increments and includes some dependence of consecutive phase ...baseline, and the ...algorithm and applied it to ECG ...estimate and maybe a worthwhile alternative to common methods for ... Voir le document complet
30
On Composition and Implementation of Sequential Consistency (Extended Version)
... update and the time when it is validated (grey zones in ...necessary and sufficient to wait either during read or during write ...operation, and second the time between the end of an update ... Voir le document complet
17
An efficient optimizer for simple point process models
... s and v L s, the average number of explorations in the neighborhood of any image ...time and precision when in an attraction ...average and thus then reachable in |M | x local ... Voir le document complet
14
Algorithms and inference for simultaneous-event multivariate point-process, with applications to neural data
... Likelihood methods based on point processes assume that either the components of the multivariate point process are independent, or that simultaneous occurrences of [r] ... Voir le document complet
118
Multi-active Objects and their Applications (extended version).
... Backend and Translational ...object and concurrency layer, plus distributed ...activities and is more ...objects and schedule their ...difficult and costly (each synchronisation should ... Voir le document complet
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