Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

Troudi, M.; Alimi, Adel M.; Saoudi, Samir

doi:10.1155/2008/739082

Cited by 38 publications

(13 citation statements)

References 7 publications

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“…The pdf f (x) is estimated by combining the algorithms proposed in [42] and [43], which employs a Gaussian kernel with zero mean and unit variancê…”

Section: Fisher-shannon Methodsmentioning

confidence: 99%

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

Guignard

Lovallo

Laib

et al. 2019

Physica A: Statistical Mechanics and its Applications

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In this paper, the time dynamics of the daily means of wind speed measured in complex mountainous regions are investigated. For 293 measuring stations distributed over all Switzerland, the Fisher information measure and the Shannon entropy power are calculated. The results reveal a clear relationship between the computed measures and both the elevation of the wind stations and the slope of the measuring sites. In particular, the Shannon entropy power and the Fisher information measure have their highest (respectively lowest) values in the Alps, where the time dynamics of wind speed follows a more disordered pattern.The spatial mapping of the calculated quantities allows the identification of two regions, which is in agreement with the topography of the Swiss territory.The present study could contribute to a better characterization of the temporal dynamics of wind speed in complex mountainous terrain.

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“…The pdf f (x) is estimated by combining the algorithms proposed in [42] and [43], which employs a Gaussian kernel with zero mean and unit variancê…”

Section: Fisher-shannon Methodsmentioning

confidence: 99%

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

Guignard

Lovallo

Laib

et al. 2019

Physica A: Statistical Mechanics and its Applications

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“…In our study, we estimated the pdf f(x) by means of the algorithm developed by Troudi et al (2008) combined with that developed in Raykar and Duraiswami (2006), that uses a Gaussian kernel with zero mean and unit variance:…”

Section: The Fisher-shannon Information Planementioning

confidence: 99%

Discriminating Between Different Streamflow Regimes by Using the Fisher-Shan Method: An Application to the Colombia Rivers

et al. 2015

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A b s t r a c tThe Fisher-Shannon (FS) information plane, defined by the Fisher information measure (FIM) and the Shannon entropy power (N X ), was robustly used to investigate the complex dynamics of eight monthly streamflow time series in Colombia. In the FS plane the streamflow series seem to aggregate into two different clusters corresponding to two different climatological regimes in Colombia. Our findings suggest the use of the statistical quantity defined by the FS information plane as a tool to discriminate among different hydrological regimes.

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“…-la méthode Plug-in Park et Marron, 1990 ;Troudi et al, 2008 ;Troudi, 2009) ; -la méthode des contrastes (Mugadi et Ahmad, 2004) ; -la méthode de diffusion linéaire (Botev et al, 2010).…”

Section: Estimateurs à Noyauunclassified

“…Cependant, la sélection d'une valeur appropriée pour le paramètre de lissage est nécessaire pour garantir une bonne qualité de l'estimation. La majorité des méthodes développées ont été proposées pour la sélection du pas optimal au sens de l'écart quadratique moyen intégré (EQMI) pour la méthode du noyau conventionnelle, les principales étant la méthode de la validation croisée et ses variantes (Bowman, 1984 ;Hall et al, 1992), les méthodes plug-in (Hall et Marron, 1992 ;Troudi et al, 2008 ;Troudi, 2009), la méthode des contrastes (Mugadi et Ahmad, 2004) et plus récemment une méthode développée par Botev, basée sur un processus de diffusion linéaire (Botev et al, 2011). Dans cet article, nous proposons d'étendre l'algorithme plug-in à la méthode du noyau difféomorphisme.…”

Section: Introductionunclassified

Extension de l’algorithme plug-in pour l’optimisation du paramètre de lissage de l’estimateur du noyau-difféomorphisme

Troudi¹,

Ghorbel²

2014

Traitement du signal

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L'estimateur noyau-difféomorphisme est une généralisation de l'estimateur à noyau permettant d'estimer les densités en tenant compte de leur support naturel. Le recours à un changement de variable approprié permet de limiter significativement le phénomène de Gibbs. Cependant, la qualité de l'estimation est tributaire de la valeur du pas qui doit être ajusté. Dans cet article, nous nous focalisons sur l'algorithme plug-in pour l'optimisation du pas. Ainsi, nous proposons une extension de cet algorithme itératif à l'estimateur du noyau difféomorphisme. Après un aperçu des théorèmes de convergence de la méthode du noyaudifféomorphisme et la présentation de l'algorithme proposé, la mesure de l'écart quadratique moyen intégré de quelques densités semi-bornées et bornées simulées puis ré-estimées permet de mettre en évidence l'intérêt de cette approche. ABSTRACT. The kernel-diffeomorphism estimate is a generalization of the kernel estimate taking into account of the natural support of estimated densities. Using a suitable change of variables can significantly limit the Gibbs phenomenon. The quality of the estimate depends on the value of the bandwidth which must be adjusted. In this article, we focus on the plug-in algorithm to optimize the bandwidth. Thus, we propose to extend it to the kerneldiffeomorphism estimate. The Mean Integrated Square Error of simulated and re-estimated bounded and semi-bounded densities highlight the interest of this approach. MOTS-CLÉS : estimateur non paramétrique, estimateur noyau-difféomorphisme, paramètre de lissage, support borné, algorithme plug-in.

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Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

Cited by 38 publications

References 7 publications

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method

Discriminating Between Different Streamflow Regimes by Using the Fisher-Shan Method: An Application to the Colombia Rivers

Extension de l’algorithme plug-in pour l’optimisation du paramètre de lissage de l’estimateur du noyau-difféomorphisme

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