Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Yousri SLAOUI"'
Publikováno v:
Entropy, Vol 25, Iss 10, p 1474 (2023)
We consider unimodal time series forecasting. We propose Gaussian and Lerch models for this forecasting problem. The Gaussian model depends on three parameters and the Lerch model depends on four parameters. We estimate the unknown parameters by mini
Externí odkaz:
https://doaj.org/article/301a4f9502c54c59a059329336a186a6
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 8 (2022)
We study in this article some statistical methods to fit some epidemiological parameters. We first consider a fit of the probability distribution which underlines the serial interval distribution of the COVID-19 on a given set of data collected on th
Externí odkaz:
https://doaj.org/article/1a261d145dfb40c4bf5224c173c3578d
Publikováno v:
Entropy, Vol 25, Iss 3, p 473 (2023)
The purpose of this paper is to propose a new algorithm based on stochastic expectation maximization (SEM) to deal with the problem of unobserved values when multiple interactions in a linear mixed-effects model (LMEM) are present. We test the effect
Externí odkaz:
https://doaj.org/article/119baa953cb849d5a65218286085a41b
Autor:
Yousri Slaoui
Publikováno v:
Opuscula Mathematica, Vol 39, Iss 5, Pp 733-746 (2019)
In this paper we prove large and moderate deviations principles for the recursive kernel estimators of a distribution function defined by the stochastic approximation algorithm. We show that the estimator constructed using the stepsize which minimize
Externí odkaz:
https://doaj.org/article/05c2114e70f44ed588ac0c0abc0fd4fe
Autor:
Céline Borras, Kimberley Delaunay, Yousri Slaoui, Toufik Abache, Sylvie Jorieux, Marie-Christine Naud, Mohamed El Sanharawi, Emmanuelle Gelize, Patricia Lassiaz, Na An, Laura Kowalczuk, Cédric Ayassami, Alexandre Moulin, Francine Behar-Cohen, Frédéric Mascarelli, Virginie Dinet
Publikováno v:
Frontiers in Immunology, Vol 11 (2020)
A common allele (402H) of the complement factor H (FH) gene is the major risk factor for age-related macular degeneration (AMD), the leading cause of blindness in the elderly population. Development and progression of AMD involves vascular and inflam
Externí odkaz:
https://doaj.org/article/3646d397d2b940178ae9e6eb1094d66d
Publikováno v:
Entropy, Vol 24, Iss 3, p 315 (2022)
The central focus of this paper is upon the alleviation of the boundary problem when the probability density function has a bounded support. Mixtures of beta densities have led to different methods of density estimation for data assumed to have compa
Externí odkaz:
https://doaj.org/article/6b2312e46c2b4a38872890092eb01a0d
Autor:
Yousri Slaoui
Publikováno v:
Journal of Probability and Statistics, Vol 2014 (2014)
We propose an automatic selection of the bandwidth of the recursive kernel estimators of a probability density function defined by the stochastic approximation algorithm introduced by Mokkadem et al. (2009a). We showed that, using the selected bandwi
Externí odkaz:
https://doaj.org/article/48322b23fc0d4876a567fc771ca9c327
Autor:
Jacqueline Milet, Gregory Nuel, Laurence Watier, David Courtin, Yousri Slaoui, Paul Senghor, Florence Migot-Nabias, Oumar Gaye, André Garcia
Publikováno v:
PLoS ONE, Vol 5, Iss 7, p e11616 (2010)
Multiple factors are involved in the variability of host's response to P. falciparum infection, like the intensity and seasonality of malaria transmission, the virulence of parasite and host characteristics like age or genetic make-up. Although admit
Externí odkaz:
https://doaj.org/article/0e40c85525214170a95b5bf46fe1c11c
Autor:
Yousri Slaoui
Publikováno v:
Monte Carlo Methods and Applications. 29:55-77
In this paper, we propose and investigate two new kernel regression estimators based on a bias reduction transformation technique. We study the properties of these estimators and compare them with Nadaraya–Watson’s regression estimator and Slaoui
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::573e604240065dd09e4131786f994bb9
https://doi.org/10.1515/mcma-2022-2130
https://doi.org/10.1515/mcma-2022-2130
Publikováno v:
Statistics, Optimization & Information Computing. 10:1021-1043
In this research paper, we set forward a non-parametric multivariate recursive kernel regression estimator under missing data using the propensity score approach in order to describe writing word production. Our main objective is to explore cognitive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e8ace6aa009a4472831a7fb27a920dd
https://doi.org/10.19139/soic-2310-5070-1507
https://doi.org/10.19139/soic-2310-5070-1507