Výsledky vyhledávání - "Diongue Abdou Ka"

Akademický článek

A classification method for binary predictors combining similarity measures and mixture models

Autor: Sylla Seydou N., Girard Stéphane, Diongue Abdou Ka, Diallo Aldiouma, Sokhna Cheikh

Publikováno v: Dependence Modeling, Vol 3, Iss 1 (2015)

In this paper, a new supervised classification method dedicated to binary predictors is proposed. Its originality is to combine a model-based classification rule with similarity measures thanks to the introduction of new family of exponential kernels

Externí odkaz: https://doaj.org/article/f7872805d6b345e7a1929aa5c79832f6

Zobrazit plný text záznamu

Report

Adaptive Realized Hyperbolic GARCH Process: Stability and Estimation

Autor: Sall, El Hadji Mamadou, Deme, El Hadji, Diongue, Abdou Kâ

In this paper, we propose an Adaptive Realized Hyperbolic GARCH (A-Realized HYGARCH) process to model the long memory of high-frequency time series with possible structural breaks. The structural change is modeled by allowing the intercept to follow

Externí odkaz: http://arxiv.org/abs/2104.14714

Zobrazit plný text záznamu

Report

Modeling Risk via Realized HYGARCH Model

Autor: Sall, El Hadji Mamadou, Deme, El Hadji, Diongue, Abdou Ka

In this paper, we propose the realized Hyperbolic GARCH model for the joint-dynamics of lowfrequency returns and realized measures that generalizes the realized GARCH model of Hansen et al.(2012) as well as the FLoGARCH model introduced by Vander Els

Externí odkaz: http://arxiv.org/abs/2104.12409

Zobrazit plný text záznamu

Akademický článek

High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype

Autor: Gaye, Aboubacry, Diongue, Abdou Ka, Komen, Lionel Nanguep, Diallo, Amadou, Sylla, Seydou Nourou, Diarra, Maryam, Talla, Cheikh, Loucoubar, Cheikh

Publikováno v: In Infectious Disease Modelling December 2023 8(4):1079-1087

Zobrazit plný text záznamu

Akademický článek

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Report

Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

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

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

Externí odkaz: http://arxiv.org/abs/1211.7262

Zobrazit plný text záznamu