Search results for "Kernel estimator"

showing 7 items of 7 documents

Gamma Kernel Intensity Estimation in Temporal Point Processes

2011

In this article, we propose a nonparametric approach for estimating the intensity function of temporal point processes based on kernel estimators. In particular, we use asymmetric kernel estimators characterized by the gamma distribution, in order to describe features of observed point patterns adequately. Some characteristics of these estimators are analyzed and discussed both through simulated results and applications to real data from different seismic catalogs.

Statistics and ProbabilityNonparametric statisticsEstimatorKernel principal component analysisPoint processVariable kernel density estimationKernel embedding of distributionsModeling and SimulationKernel (statistics)Bounded domainStatisticsGamma distributionGamma kernel estimatorIntensity functionTemporal point processes.Settore SECS-S/01 - StatisticaMathematicsCommunications in Statistics - Simulation and Computation
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Diagnostics for nonparametric estimation in space-time seismic processes

2010

In this paper we propose a nonparametric method, based on locally variable bandwidths kernel estimators, to describe the space-time variation of seismic activity of a region of Southern California. The flexible estimation approach is introduced together with a diagnostic method for space-time point process, based on the interpretation of some second-order statistics, to analyze the dependence structure of observed data and suggest directions for fit improvement. In this paper we review a diagnostic method for space-time point processes based on the interpretation of the transformed version of some second-order statistics. The method is useful to analyze dependence structures of observed dat…

Point process second-order statistics residual analysis kernel estimator seismic process.Settore SECS-S/01 - Statistica
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Nonparametric intensity estimation in space-time point processes and application to seismological problems

2008

space-time point processes intensity function kernel estimator
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Semi-parametric estimation of conditional intensity functions in inhomogeneous space-time point processes

2009

Dealing with data coming from a space-time inhomogeneous process, there is often the need of obtaining estimates of the conditional intensity function, without a complete defi nition of a parametric model and so nonparametric estimation is required: isotropic or anisotropic kernel estimates can be used. The properties of the intensities estimated are not always good, expecially in seismological field. We could try to choose the bandwidth in order to have good predictive properties of the estimated intensity function. Since a direct ML approach can not be followed, we use an estimation procedure based on the further increments of likelihood obtained adding a new observation. Similarly to cro…

conditional intensity function forward likelihood predictive estimation kernel estimatorSettore SECS-S/01 - Statistica
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Probabilistic forecast for Northern New Zealand seismic process: a kernel-based approach

2009

Forecast of earthquakes of a given area of Northern New Zealand is provided. It is based on the assumption that future earthquakes activity may be based on the smoothing of past earthquakes. Therefore, seismic activity is described by an intensity function factorized into kernel functions which depend on time longitude and latitude of events.

Forecast of seismic activity kernel estimator New Zealand seismicitySettore SECS-S/01 - Statistica
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KERNEL ESTIMATION OF THE TRANSITION DENSITY IN BIFURCATING MARKOV CHAINS

2023

We study the kernel estimator of the transition density of bifurcating Markov chains. Under some ergodic and regularity properties, we prove that this estimator is consistent and asymptotically normal. Next, in the numerical studies, we propose two data-driven methods to choose the bandwidth parameters. These methods are based on the so-called two bandwidths approach.

cross validation methodKernel estimatorrule of thumb type methodasymptotic normalitybinary trees[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]bifurcating Markov chains[STAT] Statistics [stat]
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Robust estimation of mean electricity consumption curves by sampling for small areas in presence of missing values

2017

In this thesis, we address the problem of robust estimation of mean or total electricity consumption curves by sampling in a finite population for the entire population and for small areas. We are also interested in estimating mean curves by sampling in presence of partially missing trajectories.Indeed, many studies carried out in the French electricity company EDF, for marketing or power grid management purposes, are based on the analysis of mean or total electricity consumption curves at a fine time scale, for different groups of clients sharing some common characteristics.Because of privacy issues and financial costs, it is not possible to measure the electricity consumption curve of eac…

Linear mixed modelsSmall area estimationMissing dataRegression treesEstimation sur petits domaines[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Estimateurs à noyauModèles linéaires mixtesRandom forestsBiais conditionnelsFunctional dataSurvey sampling[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]RobustesseDonnées fonctionnellesPlus proches voisinsForêts aléatoiresConditional biasKernel estimatorsNearest neighboursSondageDonnées manquantesRobustnessArbres de régression
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