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181 results on '"Diop, Aliou"'

1. Nonparametric kernel estimation of Weibull-tail coefficient in presence of the right random censoring

Author

Rutikange, Justin Ushize and Diop, Aliou

Subjects
Statistics - Methodology, Mathematics - Statistics Theory, Statistics - Computation
Abstract

In this paper, nonparametric estimation of the conditional Weibull-tail coefficient when the variable of interest is right random censored is addressed. A Weissman-type estimator of conditional extreme quantile is also proposed. In addition, a simulation study is conducted to assess the finite-sample behavior of the proposed estimators and a comparison with alternative strategies is provided. Finally, the practical applicability of the methodology is presented using a real datasets of men suffering from a larynx cancer.

Published
2021

2. Zero-inflated generalized extreme value regression model for binary data and application in health study

Author

Diop, Aba, Deme, El Hadji, and Diop, Aliou

Subjects
Statistics - Methodology
Abstract

Logistic regression model is widely used in many studies to investigate the relationship between a binary response variable $Y$ and a set of potential predictors $\mathbf X$. The binary response may represent, for example, the occurrence of some outcome of interest ($Y=1$ if the outcome occurred and $Y=0$ otherwise). When the dependent variable $Y$ represents a rare event, the logistic regression model shows relevant drawbacks. In order to overcome these drawbacks we propose the Generalized Extreme Value (GEV) regression model. In particular, we suggest the quantile function of the GEV distribution as link function, so our attention is focused on the tail of the response curve for values close to one. A sample of observations is said to contain a cure fraction when a proportion of the study subjects (the so-called cured individuals, as opposed to the susceptibles) cannot experience the outcome of interest. One problem arising then is that it is usually unknown who are the cured and the susceptible subjects, unless the outcome of interest has been observed. In these settings, a logistic regression analysis of the relationship between $\mathbf X$ and $Y$ among the susceptibles is no more straightforward. We develop a maximum likelihood estimation procedure for this problem, based on the joint modeling of the binary response of interest and the cure status. We investigate the identifiability of the resulting model. Then, we conduct a simulation study to investigate its finite-sample behavior, and application to real data.

Published
2021

7. Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions

Author

Ahmad Aboubacrène Ag, Deme El Hadji, Diop Aliou, and Girard Stéphane

Subjects
nonparametric estimation, location-scale function, tail-index, extreme-values, conditional quantile, 62g05, 62g08, 62g32, Science (General), Q1-390, Mathematics, QA1-939
Abstract

We introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced. Second, an estimator of the conditional extreme-value index is derived. The asymptotic properties of the estimators are established under mild assumptions and their finite sample properties are illustrated both on simulated and real data.

Published
2019
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8. Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Author

Ndongo, Mor, Diongue, Abdou Kâ, Diop, Aliou, and Dossou-Gbété, Simplice

Subjects
Mathematics - Statistics Theory
Abstract

Maximum likelihood methods, while widely used, may be non-robust due to disagreement between the assumptions upon which the models are based and the true density probability distribution of observed data. Because the Empirical Characteristic Function (ECF) is the Fourier transform of the empirical distribution function, it retains all the information in the sample but can overcome difficulties arising from the likelihood. This paper discusses an estimation method via the ECF for stable seasonal fractional ARIMA processes. Under some assumptions, we show that the resulting estimators are consistent and asymptotically normally distributed. For comparison purpose, we consider also the MCMC Whittle method developed by Ndongo et al. (2010). The performance of the two methods is discussed using a Monte Carlo simulation.

Published
2012

9. Classification approach based on association rules mining for unbalanced data

Author

Ndour, Cheikh, Diop, Aliou, and Dossou-Gbété, Simplice

Subjects
Statistics - Machine Learning, Computer Science - Learning
Abstract

This paper deals with the binary classification task when the target class has the lower probability of occurrence. In such situation, it is not possible to build a powerful classifier by using standard methods such as logistic regression, classification tree, discriminant analysis, etc. To overcome this short-coming of these methods which yield classifiers with low sensibility, we tackled the classification problem here through an approach based on the association rules learning. This approach has the advantage of allowing the identification of the patterns that are well correlated with the target class. Association rules learning is a well known method in the area of data-mining. It is used when dealing with large database for unsupervised discovery of local patterns that expresses hidden relationships between input variables. In considering association rules from a supervised learning point of view, a relevant set of weak classifiers is obtained from which one derives a classifier that performs well., Comment: 29 pages

Published
2012

10. On the Generalized Hill Process for Small Parameters and Applications

Author

Lo, Gane Samb, Deme, El Hadji, and Diop, Aliou

Subjects
Statistics - Methodology, Primary : 62E20, 62F12, 60F05. Secondary : 60B10, 60F17
Abstract

Let $X_{1},X_{2},...$ be a sequence of independent copies (s.i.c) of a real random variable (r.v.) $X\geq 1$, with distribution function $df$ $F(x)=\mathbb{P}% (X\leq x)$ and let $X_{1,n}\leq X_{2,n} \leq ... \leq X_{n,n}$ be the order statistics based on the $n\geq 1$ first of these observations. The following continuous generalized Hill process {equation*} T_{n}(\tau)=k^{-\tau}\sum_{j=1}^{j=k}j^{\tau}(\log X_{n-j+1,n}-\log X_{n-j,n}), \label{dl02} {equation*} $\tau >0$, $1\leq k \leq n$, has been introduced as a continuous family of estimators of the extreme value index, and largely studied for statistical purposes with asymptotic normality results restricted to $\tau > 1/2$. We extend those results to $0 < \tau \leq 1/2$ and show that asymptotic normality is still valid for $\tau=1/2$. For $0 < \tau <1/2$, we get non Gaussian asymptotic laws which are closely related to the Riemann function $% \zeta(s)=\sum_{n=1}^{\infty} n^{-s},s>1$, Comment: 19 pages; 4 figures

Published
2011

12. Introduction aux probabilités discrètes et à la statistique descriptive : Cours et exercices

Author

Diop, Aliou, Diop, Assane, Sagna, Abass, Diop, Aliou, Diop, Aliou, Diop, Assane, Sagna, Abass, and Diop, Aliou

Abstract

Cet ouvrage aborde le programme de la première année universitaire et entame une bonne partie du programme de la deuxième année en Probabilités et Statistiques des filières mathématiques, physiques, chimiques, et de façon plus générale, des filières scientifiques. Ainsi, ce livre peut être utilisé par tout étudiant qui fait ses premiers pas en Probabilité et Statistique descriptive ou qui souhaite revisiter les connaissances déjà acquises dans ces domaines ou les renforcer. Il peut aussi servir de support d'enseignement. Pour faciliter la compréhension des définitions et des résultats, nous nous sommes efforcés, tout au long des chapitres, de donner des exemples ou des applications à la suite de chaque définition et résultat. Nous avons aussi proposé des exercices à la fin de chaque chapitre.

Published
2022

21. Conditional tail and quantile estimation for real-valued β-mixing spatial data

Author

Tchazino, Tchamiè, Diop, Aliou, Dabo-Niang, Sophie, Tchazino, Tchamiè, Université d’Abomey-Calavi = University of Abomey Calavi (UAC), University Gaston Berger, LERSTAD, Saint-Louis, Senegal (UGB), MOdel for Data Analysis and Learning (MODAL), Laboratoire Paul Painlevé (LPP), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), and Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-École polytechnique universitaire de Lille (Polytech Lille)

Subjects
[STAT]Statistics [stat], spatial dependence, Asymptotic normality, conditional extreme value index, β-mixing, functional estimation, bias correction, [STAT] Statistics [stat]
Abstract

This paper deals with the estimation of the tail index of a conditionnal heavy-tailed distribution of a spatial process. We are particularly interested in the estimation of conditionnal spatial rare events when the process is β−mixing. Given a conditionnal stationary real-valued multidimensional spatial process Y x i , i ∈ Z N , we investigate its conditional heavy-tail index estimation and the corresponding conditional quantile. Asymptotic properties of the corresponding estimators are established under mild mixing conditions. The particularity of the tail proposed estimator is based on the spatial nature of the sample and its unbiased and reduced variance properties compared to well known conditional tail index estimators. A numerical study on synthetic and real datasets is conducted to assess the finite-sample behaviour of the proposed estimators.

Published
2022

22. Tail and quantile estimation for real-valued β-mixing spatial data

Author

TCHAZINO, Tchamiè, Dabo-Niang, Sophie, Diop, Aliou, MOdel for Data Analysis and Learning (MODAL), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Paul Painlevé - UMR 8524 (LPP), Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-École polytechnique universitaire de Lille (Polytech Lille)-Université de Lille, Sciences et Technologies, DAAD et CEA-SMIA, Laboratoire Paul Painlevé (LPP), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-École polytechnique universitaire de Lille (Polytech Lille), and Tchazino, Tchamiè

Subjects
[STAT]Statistics [stat], functional estimation, spatial dependence, extreme value index, Asymptotic normality, [MATH] Mathematics [math], β-mixing, [MATH]Mathematics [math], bias correction, [STAT] Statistics [stat]
Abstract

This paper deals with extreme-value index estimation of a heavy-tailed distribution of a spatial dependent process. We are particularlyinterested in spatial rare events of a β−mixing process. Given a sta-tionary real-valued multidimensional spatial process {X_i,i ∈ Z^N}, weinvestigate its heavy-tail index estimation. Asymptotic properties ofthe corresponding estimator are established under mildmixingcondi-tions. The particularity of the tail proposed estimator is based on thespatial nature of the sample and its unbiased and reduced variance prop-erties compared to well known tail index estimators. Extreme quantileestimation is also deduced. A numerical study on synthetic and realdatasets is conducted to assess the finite-sample behaviour of the pro-posed estimators.

Published
2021

24. Zero-inflated generalized extreme value regression model for binary response data and application in health study.

Author

Diop, Aba, Deme, El Hadji, and Diop, Aliou

Subjects
EXTREME value theory, QUANTILE regression, REGRESSION analysis, LOGISTIC regression analysis, MAXIMUM likelihood statistics, DEPENDENT variables
Abstract

Binary responses are often present in medical studies. When the dependent variable Y represents a rare event, the logistic regression model shows relevant drawbacks. To overcome these drawbacks, we propose the quantile function of the generalized extreme value regression distribution as a link function and focus our attention on values close to one. One problem arising in the presence of cure fraction is that, it is usually unknown who are the cured and the susceptible subjects, unless the outcome of interest has been observed. In these settings, a logistic regression analysis is no more straightforward. We develop a maximum likelihood estimation procedure, based on the joint modeling of the binary response of interest and the cure status. We investigate the identifiability of the resulting model and establish the asymptotic properties. We conduct a simulation study to investigate its finite-sample behaviour, and application to real data. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Tail and Quantile Estimation for Real-Valued -Mixing Spatial Data.

Author

Tchazino, Tchamiè, Dabo-Niang, Sophie, and Diop, Aliou

Abstract

This paper deals with extreme-value index estimation of a heavy-tailed distribution of a spatial dependent process. We are particularly interested in spatial rare events of a -mixing process. Given a stationary real-valued multidimensional spatial process , we investigate its heavy-tail index estimation. Asymptotic properties of the corresponding estimator are established under mild mixing conditions. The particularity of the tail proposed estimator is based on the spatial nature of the sample and its unbiased and reduced variance properties compared to well known tail index estimators. Extreme quantile estimation is also deduced. A numerical study on synthetic and real datasets is conducted to assess the finite-sample behaviour of the proposed estimators. [ABSTRACT FROM AUTHOR]

Published
2022
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27. A constrained marginal zero-inflated binomial regression model.

Author

Ali, Essoham, Diop, Aliou, and Dupuy, Jean-François

Subjects
*BINOMIAL theorem, *REGRESSION analysis, *MAXIMUM likelihood statistics, *MODELS (Persons)
Abstract

Zero-inflated models have become a popular tool for assessing relationships between explanatory variables and a zero-inflated count outcome. In these models, regression coefficients have latent class interpretations, where latent classes correspond to a susceptible subpopulation with observations generated from a count distribution and a non susceptible subpopulation that provides only zeros. However, it is often of interest to evaluate covariates effects in the overall mixture population, that is, on the marginal mean of the zero-inflated count. Marginal zero-inflated models, such as the marginal zero-inflated Poisson models, have been developed for that purpose. They specify independent submodels for the susceptibility probability and the marginal mean of the count response. When the count outcome is bounded, it is tempting to formulate a marginal zero-inflated binomial model in the same fashion. This, however, is not possible, due to inherent constraints that relate, in the zero-inflated binomial model, the susceptibility probability and the latent and marginal means of the count outcome. In this paper, we propose a new marginal zero-inflated binomial regression model that accommodates these constraints. We investigate the maximum likelihood estimator in this model, both theoretically and by simulations. An application to the analysis of health-care demand is provided for illustration. [ABSTRACT FROM AUTHOR]

Published
2022
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30. Estimation of extreme tail index for β−mixing random fields

Author

Tchamie, Tchazino, Dabo-Niang, Sophie, Diop, Aliou, Dabo-Niang, Sophie, Institut de Mathématiques et de Sciences Physiques (IMSP), Université d’Abomey-Calavi = University of Abomey Calavi (UAC), MOdel for Data Analysis and Learning (MODAL), Laboratoire Paul Painlevé (LPP), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-École polytechnique universitaire de Lille (Polytech Lille), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Université Gaston Berger de Saint-Louis Sénégal (UGB), Institut de Mathématiques et de Sciences Physiques [Bénin] (Université d’Abomey-Calavi (UAC)) (IMSP), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Paul Painlevé - UMR 8524 (LPP), Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-École polytechnique universitaire de Lille (Polytech Lille)-Université de Lille, Sciences et Technologies, and Laboratoire Paul Painlevé - UMR 8524 (LPP)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]
Published
2021

31. Data Geometry and Extreme Value Distribution

Author

Cisse , Mamadou, Diop , Aliou, Bognini , Souleymane, ALAHASSA, Nonvikan Karl-Augustt, Cisse , Mamadou, Diop , Aliou, Bognini , Souleymane, and ALAHASSA, Nonvikan Karl-Augustt

Abstract

In extreme values theory, there exist two approaches about data treatment: block maxima and peaks-over-threshold (POT) methods, which take in account data over a fixed value. But, those approaches are limited. We show that if a certain geometry is modeled with stochastic graphs, probabilities computed with Generalized Extreme Value (GEV) Distribution can be deflated. In other words, taking data geometry in account change extremes distribution. Otherwise, it appears that if the density characterizing the states space of data system is uniform, and if the quantile studied is positive, then the Weibull distribution is insensitive to data geometry, when it is an area attraction, and the Fréchet distribution becomes the less inflationary.

Published
2021

35. Characteristics of the herbaceous vegetation of an exclosure in Ferlo North in Senegal

Author

Bassene, C, Dalanda DIALLO, Mariama, Diaité, Bakary, Diop, Aliou, Guissé, Aliou, Environnement, Santé, Sociétés (ESS), Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0010/11-LABX-0010,LabEx DRIIHM,Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux(2011), Duboz, Priscilla, and Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux - - DRIIHM / IRDHEI2011 - ANR-11-LABX-0010 - LABX - VALID

Subjects
[SDE] Environmental Sciences, Observatoires Hommes-Millieux, OHMi Tessekere, LabEx DRIIHM, [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

36. Extreme value mixture model under random censoring over the threshold

Author

LOUM, Mor Absa, Diop, Aliou, Laboratoire de Mathématiques d'Orsay (LMO), Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), laboratoire d'Etudes et de recherches en Statistiques et Développement (LERSTAD), and Université Gaston Bergé Sénégal

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Extreme value theory, Random censoring, Extreme value mixture, Maximum likelihood
Abstract

In this paper, we propose in this study a likelihood maximization method to estimate the extreme value mixture model parameters under random censoring. The idea is a combination of two maximization steps. We consider a mixture model with two components: A Weibull distribution below the threshold u (above which the data are considered extreme) and a Generalized Pareto Distribution under random cen-soring above the threshold. We present our estimation method in two steps: (1) first, likelihood maximization for a given threshold, (2) secondly, likelihood maximization under different thresholds. We start by presenting the model and the estimation method. Finite-sample behavior of the estimator is assessed via simulations.

Published
2020

37. Effet de l'application de différentes doses de fertilisants organiques sur la croissance et le rendement de la tomate (Solanum lycopersicum)

Author

Diaité, Bakary, Dalanda DIALLO, Mariama, Goalbaye, Touroumgaye, Diédhiou, Siré, Diallo, Abdourahmane, Talla, Ramata, Diop, Aliou, Guissé, Aliou, Environnement, Santé, Sociétés (ESS), Centre National de la Recherche Scientifique (CNRS), UFR des Sciences Agronomiques de l'Aquaculture et des Technologies Alimentaires, Université Gaston Berger de Saint-Louis Sénégal (UGB), Université de Sarh, Université Assane SECK de Ziguinchor (UASZ), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), and ANR-11-LABX-0010,DRIIHM / IRDHEI,Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux(2011)

Subjects
Sénégal, Solanum lycopersicum, litter, growth, litière, dose, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, rendement, yield, croissance, Senegal
Abstract

International audience; L'objectif de cette étude est d’évaluer les effets de l'application de différents fertilisants organiques (fumier de vache, litières de Balanites aegyptiaca (L.) Del., Boscia senegalensis (Pers.) Lam. ex Poir. et Sclerocarya birrea (A. Rich.) Hochst) sur les paramètres de croissance et de rendement de la variété F1 Mongal de la tomate (Solanum lycopersicum L.) en conditions semi-contrôlées. L’étude a été effectuée à la ferme agricole de l’Université Gaston Berger de Saint Louis au Nord du Sénégal entre avril et juin 2018. Le dispositif expérimental utilisé est en blocs aléatoires randomisés avec quatre (04) répétitions, huit (08) traitements et trois (03) doses (0,2%, 0,5% et 0,8%). Les traitements appliqués sont : T0 (témoin sans apport de fertilisant), T1 (litière de Balanites aegyptiaca), T2 (litière de Boscia senegalensis), T3 (litière de Sclerocarya birrea), T4 (fumier), T5, T6 et T7 (mélange à proportion égale (½+ ½) de fumier et chacune des trois (03) litières). Après application des différents fertilisants organiques, une durée de décomposition de 15 jours a été observée avant semis dans des pots de 1,5 kg. Après 60 jours de croissance, les résultats obtenus ont montré que les effets sur la croissance de la tomate varient en fonction de la dose et de la qualité de la matière organique apportée. Les litières de B. senegalensis appliquées seules ou en combinaison avec le fumier et la litière B. aegyptiaca utilisée seule ont amélioré significativement certains des paramètres étudiés (hauteur, surface foliaire, biomasse sèche aérienne et couleur du feuillage) aux doses de 0,5% et 0,8%. Les meilleurs effets ont été induits par la plus forte dose (0,8%) de B. senegalensis. La litière de S. birrea n’a pas eu d’effets significatifs sur les paramètres de croissance et de rendements de la tomate. Le fumier n’a montré aucun effet sur les paramètres de croissance de la tomate par rapport au témoin sans fertilisant. Ainsi, la litière de B. senegalensis dans les conditions de cet essai, a montré un grand potentiel pour l’amélioration des paramètres de croissance et de rendement de la tomate.

Published
2020

46. Agronomic valuation of the bedding of some plant species of the Great Green Wall of Ferlo

Author

Diallo, Mariama Dalanda, Diaité, Bakary, Diop, Aliou, Guissé, Aliou, Université Gaston Berger de Saint-Louis Sénégal (UGB), Laboratoire Ecologie Végétale (UCAD), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), ENS, ANR-11-LABX-0010,DRIIHM / IRDHEI,Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux(2011), Pardo, Corinne, and Dispositif de recherche interdisciplinaire sur les Interactions Hommes-Milieux - - DRIIHM / IRDHEI2011 - ANR-11-LABX-0010 - LABX - VALID

Subjects
OHMi Tessekere, [SDE.ES] Environmental Sciences/Environmental and Society, [SDE.ES]Environmental Sciences/Environmental and Society, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

47. Effets de l'application de différents fertilisants sur la fertilité des sols, la croissance et le rendement du mil (Pennisetum glaucum (L.) R. Br. dans la Commune de Gandon au Sénégal

Author

Diallo, Mariama Dalanda, Diaité, Bakary, Diédhiou, Papa Madiallacké, Diédhiou, Sire, Goalbaye, Touroumgaye, Doelsch, Emmanuel, Diop, Aliou, and Guisse, Aliou

Subjects
Engrais organique, F08 - Systèmes et modes de culture, Déchet d'exploitation forestière, Casuarina equisetifolia, Rendement des cultures, Faidherbia albida, Engrais vert, Pennisetum glaucum, F04 - Fertilisation
Abstract

Description du sujet. Au Sénégal, les sols sont généralement de texture sableuse, caractérisés par une faible teneur en éléments nutritifs avec une incidence directe sur les rendements des cultures. Une meilleure option de fertilisation basée sur la disponibilité de la matière organique locale a pour effet d'augmenter la production agricole. Objectifs. L'objectif de cette étude est d'évaluer les effets de l'application de différentes matières organiques (compost, litières de Faidherbia albida A. CHEV. et de Casuarina equisetifolia FORSK.) et minérale (N-P-K 10-10-20 et urée 46%) sur la fertilité du sol, la croissance et le rendement de la variété Souna 3 du mil (Pennisetum glaucum (L.) R. Br.). Méthodes. L'étude a été effectuée à la ferme agricole de l'Université Gaston Berger de Saint Louis au Nord du Sénégal, au cours de la saison pluvieuse de l'année 2016. Le dispositif expérimental utilisé était le plan en blocs aléatoires randomisés avec quatre répétitions et six traitements. Les traitements appliqués sont : T0 (témoin sans apport de fertilisant), T1 (N-P-K 10-10-20 150 kg ha-1 et l'urée 100 kg ha-1), T2 (litière de F. albida 5 t ha-1), T3 (litière de C. equisetifolia 5 t ha-1), T4 (2,5 t ha-1 des litières de F. albida + 2,5 t ha-1 de C. equisetifolia), et T5 (compost à base de résidus végétaux et de déjections animales 10 t ha-1). Résultats. Les résultats obtenus ont montré que le traitement à base de la fertilisation minérale (T1) a significativement influencé la croissance en hauteur (p= 0,056), les biomasses aérienne (p= 0,0281) et racinaire (p= 0,0374) et le rendement en grains du mil (p= 0,0015) comparativement au témoin (T0) au seuil de 5%. Les autres traitements n'ont pas montré d'effets significatifs par rapport au témoin concernant la croissance et le rendement du mil. Le rendement le plus élevé obtenu était de 1656,70±349,20 kg ha-1 (T1). Conclusion. Les études sur l'utilisation de ces matières en grande culture sont nécessaires avant la diffusion de cette technologie en milieux paysans.

Published
2019

48. A new location-scale model for conditional heavy-tailed distributions

Author

Ahmad, Aboubacrène Ag, Diop, Aliou, Deme, EL Hadji, Girard, Stéphane, Université Gaston Berger de Saint-Louis Sénégal (UGB), laboratoire d'Etudes et de recherches en Statistiques et Développement (LERSTAD), Université Gaston Bergé Sénégal, Modelling and Inference of Complex and Structured Stochastic Systems (MISTIS ), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Laboratoire Jean Kuntzmann (LJK ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Abstract

International audience; We are interested in a location-scale model for heavy-tailed distributions where the covariate is deterministic. We first address the nonparametric estimation of the location and scale functions and derive an estimator of the conditional extreme-value index. Second, new estimators of the extreme conditional quantiles are introduced. The asymptotic properties of the estimators are established under mild assumptions.

Published
2018

49. Future Climate Change Impacts on Streamflows of Two Main West Africa River Basins: Senegal and Gambia

Author

Bodian, Ansoumana, Dezetter, A., Diop, Lamine, Deme, Abdoulaye, Djaman, Koffi, Diop, Aliou, Girardel - Laboratoire Leïdi (Leïdi), Université Gaston Berger de Saint-Louis Sénégal (UGB), Hydrosciences Montpellier (HSM), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), laboratoire d'Etudes et de recherches en Statistiques et Développement (LERSTAD), Université Gaston Bergé Sénégal, Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL)

Subjects
RELATION, Senegal River Basin, CALIBRAGE, MODELE GR4J, Gambia River Basin, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, lcsh:Science, TEMPERATURE, EVAPOTRANSPIRATION POTENTIELLE, rainfall-runoff modeling, ETALONNAGE, MODELISATION, EVOLUTION, DEBIT, COURS D'EAU, climate change, BASSIN FLUVIAL, PLUIE, PRECIPITATION, CHANGEMENT CLIMATIQUE, SIMULATION, GR4J, lcsh:Q, streamflow, VARIATION JOURNALIERE, METHODOLOGIE
Abstract

This research investigated the effect of climate change on the two main river basins of Senegal in West Africa: the Senegal and Gambia River Basins. We used downscaled projected future rainfall and potential evapotranspiration based on projected temperature from six General Circulation Models (CanESM2, CNRM, CSIRO, HadGEM2-CC, HadGEM2-ES, and MIR005) and two scenarios (RCP4.5 and RCP8.5) to force the GR4J model. The GR4J model was calibrated and validated using observed daily rainfall, potential evapotranspiration from observed daily temperature, and streamflow data. For the cross-validation, two periods for each river basin were considered: 1961-1982 and 1983-2004 for the Senegal River Basin at Bafing Makana, and 1969-1985 and 1986-2000 for the Gambia River Basin at Mako. Model efficiency is evaluated using a multi-criteria function (F-agg) which aggregates Nash and Sutcliffe criteria, cumulative volume error, and mean volume error. Alternating periods of simulation for calibration and validation were used. This process allows us to choose the parameters that best reflect the rainfall-runoff relationship. Once the model was calibrated and validated, we simulated streamflow at Bafing Makana and Mako stations in the near future at a daily scale. The characteristic flow rates were calculated to evaluate their possible evolution under the projected climate scenarios at the 2050 horizon. For the near future (2050 horizon), compared to the 1971-2000 reference period, results showed that for both river basins, multi-model ensemble predicted a decrease of annual streamflow from 8% (Senegal River Basin) to 22% (Gambia River Basin) under the RCP4.5 scenario. Under the RCP8.5 scenario, the decrease is more pronounced: 16% (Senegal River Basin) and 26% (Gambia River Basin). The Gambia River Basin will be more affected by the climate change.

Published
2018

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