Zobrazeno 1 - 10 of 36 pro vyhledávání: '"Ouagnina Hili"'
1
On Nonparametric Estimation of a Nonparametric Autoregressive Conditionally Heteroscedastic Process
Autor: Ben Célestin Kouassi, Ouagnina Hili, Edoh Katchekpele
Publikováno v: Afrika Statistika. 17:3293-3319
Since the studies of Engel (1982) and Bollerslev (1986), the ARCH and GARCH processes have been used extensively to model volatile series. However, Pagan and Schwert (1990) have shown the limits of these choices. This deficiency is overcome by the No
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::33fae43f767b26d1be09ef50ee91c902
https://doi.org/10.16929/as/2022.3318.307
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2
On Nonparametric Conditional Quantile Estimation for Non-stationary Random
Autor: Ben Célestin Kouassi, Ouagnina Hili, Edoh Katchekpele
Publikováno v: Afrika Statistika. 17:3293-3319
Since the studies of Engel (1982) and Bollerslev (1986), the ARCH and GARCH processes have been used extensively to model volatile series. However, Pagan and Schwert (1990) have shown the limits of these choices. This deficiency is overcome by the No
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d60acac536227994813d44dec7f55ef7
https://doi.org/10.16929/as/2022.3293.307
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3
Asymptotic normality for kernel weighted averages estimation
Autor: Brahima Soro, Ouagnina Hili
Publikováno v: Afrika Statistika. 17:3237-3257
This paper presents a set of general normality results for kernel weighted averages. We extend existing results in literature for independent data a s in Yao (2017) to stationary dependent longitudinal data. The asymptotic properties of the proposed
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::945a2b4b5cbe6f1620bf7c681a722fc2
https://doi.org/10.16929/as/2022.3237.305
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5
M-Estimate for the stationary hyperbolic GARCH models
Autor: Assi N'Guessan, Lanciné Bamba, Abdou Kâ Diongue, Ouagnina Hili
Publikováno v: METRON. 79:303-351
In this manuscrit, we propose two classes of M-estimates for the hyperbolic GARCH models. The first class called M-estimate is defined by minimizing of a convenient bounded loss function. The second, called BM-estimate is a modified version of the fi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c8a5552dccf431f704cbe0a726664ef1
https://doi.org/10.1007/s40300-021-00221-w
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6
Parametric Estimation of Long Memory Multivariate Gaussian random fields
Autor: Amadou Kamagate, Ouagnina Hili, Aubin Yao N'dri
Publikováno v: Afrika Statistika. 16:2747-2761
Le but de ce papier est d'etudier de facon theorique l'estimateur du minimum de distance de Hellinger des champs aleatoires multivaries, gaussiens, stationnaires, isotropes a longue memoire.Les variables sont observees sur un ensemble fini de points
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e6d6f1e59de3e15b095f9cb0907cdc6
https://doi.org/10.16929/as/2021.2745.182
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9
On Nonparametric Conditional Quantile Estimation for Non-stationary Random
Autor: Serge-Hippolyte Arnaud Kanga, Ouagnina Hili, Sophie Dabo-Niang
Publikováno v: Afrika Statistika
Afrika Statistika, 2021, 16 (4), pp.3009-3039. ⟨10.16929/as/2021.3009.193⟩
International audience; A kernel conditional quantile estimate of a real-valued non-stationary spatial process is proposed for a prediction goal at a non-observed location of the underlying process. The originality is based on the ability to take int
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6939c32ccaf1b31ef946c714d77fddc
https://inria.hal.science/hal-03527760
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10
Hellinger Distance Estimation of Strongly Dependent Gaussian Random Fields
Autor: Gueï Cyrille Okou, Aubin Yao N'dri, Ouagnina Hili
Publikováno v: Afrika Statistika; Vol 14, No 1 (2019); 1937-1950
Afr. Stat. 14, no. 1 (2019), 1937-1950
The Minimum Hellinger Distance Estimator (MHDE) of density function is investigated for stationary long memory (long-range dependent) random fields observed over a finite set of spatial points. A general result on the consistency of the MHD Estimator
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c64daa660aac082f04952b2d283b5d7d
https://doi.org/10.16929/as/2019.1937.143
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