Search results for " Statistics"

Item Response Trees: a recommended method for analyzing categorical data in behavioral studies

2015

Behavioral data are notable for presenting challenges to their statistical analysis, often due to the difficulties in measuring behavior on a quantitative scale. Instead, a range of qualitative alternative responses is recorded. These can often be understood as the outcome of a sequence of binary decisions. For example, faced by a predator, an individual may decide to flee or stay. If it stays, it may decide to freeze or display a threat and if it displays a threat, it may choose from several alternative forms of display. Here we argue that instead of being analyzed using traditional nonparametric statistics or a series of separate analyses split by response categories, this kind of data ca…

Optimisation d’un modèle atmosphérique transnational de prédiction de la concentration journalière d’ozone : intégration de paramètres météorologique…

2021

International audience; L'ozone (O3) est un polluant atmosphérique secondaire formé lors de réactions photochimiques, en présence de précurseurs (NOx, COV, CO). L'exposition à l'O3 est délicate à modéliser car ce polluant présente une forte variabilité spatiotemporelle. Le but des présents travaux est d'optimiser l'évaluation des concentrations journalières d'O3 modélisées à échelle kilométrique, à l'aide de modèles MARS et de données météorologiques. La plateforme de modélisation PREVEST a généré une prédiction de concentrations maximales journalières d'O3 pour un maillage de 3km de côté. La station de mesure de la qualité de l'air du réseau ATMO-Bourgogne-Franche-Comté, Besançon-Prévoyanc…

L'évolution de l'occupation humaine : l'analyse spatiale exploratoire des données.Le problème de l'incertitude et de l'hétérogénéité des données en a…

2011

The analysis of the evolution of the settlement requires a lot of methodological questioning. Despite a frequent use of the spatial analysis methods, few works return to their methodological problems. This article proposes to make a comparison and a discussion around two exploratory statistical methods (the K function of Ripley and the Kernel Density Estimation). It seems that scale, quality and quantity of input data, are three essential parameters to be taken into account so as to lead a spatial analysis in archaeology. In intrinsic way, archaeological data are non homogeneous. For that purpose, our article proposes a multi scalar approach integrating the non homogeneousness character of …

On the discreet spectrum of fractional quantum hydrogen atom in two dimensions

2019

We consider a fractional generalization of two-dimensional (2D) quantum-mechanical Kepler problem corresponding to 2D hydrogen atom. Our main finding is that the solution for discreet spectrum exists only for $\mu>1$ (more specifically $1 < \mu \leq 2$, where $\mu=2$ corresponds to "ordinary" 2D hydrogenic problem), where $\mu$ is the L\'evy index. We show also that in fractional 2D hydrogen atom, the orbital momentum degeneracy is lifted so that its energy starts to depend not only on principal quantum number $n$ but also on orbital $m$. To solve the spectral problem, we pass to the momentum representation, where we apply the variational method. This permits to obtain approximate analytica…

Estimating finite mixtures of semi-Markov chains: an application to the segmentation of temporal sensory data

2019

Summary In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi-Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixtur…

Investigating Long-Range Dependence in E-Commerce Web Traffic

2016

This paper addresses the problem of investigating long-range dependence (LRD) and self-similarity in Web traffic. Popular techniques for estimating the intensity of LRD via the Hurst parameter are presented. Using a set of traces of a popular e-commerce site, the presence and the nature of LRD in Web traffic is examined. Our results confirm the self-similar nature of traffic at a Web server input, however the resulting estimates of the Hurst parameter vary depending on the trace and the technique used.

Economic Crisis, worker’s health and social protection

2023

Objective The aim of this paper is to analyse the individual and contextual factorsthat could affect worker’s mental and physical health during economic downturn.This paper fills the gap in the literature that addresses the link between crisis,physical and mental health.Methods Bivariate, machine learning method and multi-level regression analysiswere performed to explore the determinants of European Worker’s mental andphysical health. Machine learning method is dedicated to the predictors ofmental and physical health problems based on a classification algorithm,random forest model. Since the respondents of our data come from differentEuropean countries, the database has a hierarchical form…

Modélisation des objets historiques selon la fonction, l'espace et le temps pour l'étude des dynamiques urbaines dans la longue durée

2010

The proposed principle for understanding the urban fabric is based on considering the town as a set of complex objects, taking a systemic approach. The town system used to study the urban fabric over large time spans is composed of three sub-systems relating to historical objects from the level of the excavation to that of the former urban space: function (social use), space (location, surface area and morphology) and time (dating, duration and chronology). The historical object is the analytical unit of the space studied. The purposed model allows urban changes to be observed. The originality of this procedure lies in its approach whereby it is possible to start not from the mapping of a p…

An approach to hypothesis testing based on local indicators of spatio-temporal association

The detection of clustering structure in a point pattern is one of the major focus of attention in spatio-temporal data mining. For instance, statistical tools for clustering detection and identification of events belonging to clusters are welcome in epidemiology and seismology. Local second-order statistics can provide information on how an event relates to nearby events. We extend local indicators of spatial association (known as LISA functions) into the spatio-temporal context (which then will be called LISTA functions). These functions can be used for local tests in the context of case-control spatio-temporal point patterns, and are able to assess in the neighbourhood of each event if t…

Spectral dynamics of incoherent waves with a noninstantaneous nonlinear response

2013

We study the influence of a constant background noise on the dynamics of spectral incoherent solitons, which are incoherent structures sustained by a noninstantaneous (Raman-like) nonlinearity. As the level of the noise background increases, the incoherent wave enters a novel nonlinear regime characterized by oscillatory dynamics of the incoherent spectrum, which develop within a spectral cone during the propagation. In contrast to the conventional Raman-like spectral red shift, such incoherent spectral dynamics can be characterized by a significant spectral blue shift. On the basis of the kinetic wave theory, we derive explicit analytical expressions of these incoherent oscillatory spectra…