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Statistics & Probability
Christian M. Dahl, Emma M. Iglesias
Summary: The study demonstrates the consistency and asymptotic normality of the maximum likelihood estimator in the level-effect ARCH model, as well as its applicability in finite samples through simulations.
STATISTICAL PAPERS
(2021)
Article
Computer Science, Artificial Intelligence
Houping Xiao, Shiyu Wang
Summary: This paper proposes a unified truth discovery algorithm, which uses maximum likelihood estimation to estimate source reliability and truth values. It proves the consistency of the estimation and the convergence of the algorithm, and conducts experiments to support the theoretical results.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Economics
Demian Pouzo, Zacharias Psaradakis, Martin Sola
Summary: This paper investigates the consistency and local asymptotic normality of maximum likelihood (ML) estimation in a large class of models with hidden Markov regimes. The models consider autoregressive dynamics in the observable process, Markov regime sequences with covariate-dependent transition matrices, and possible model misspecification. A Monte Carlo study examines the finite-sample properties of the ML estimator in correctly specified and misspecified models, and an empirical application is also discussed.
Article
Computer Science, Information Systems
Benchao Wang, Pan Qin, Hong Gu
Summary: This paper investigates the asymptotic properties of the maximum likelihood estimates of the Gamma distribution based generalized linear model (GaGLM). The score function and the Fisher information matrix for GaGLM are derived, and the asymptotic normality of the MLE is proven. Numerical results demonstrate the convergence of the MLE to a normal distribution.
Article
Statistics & Probability
Yakoub Boularouk, Jean-Marc Bardet
Summary: This study proposes a Generalized Gaussian Quasi-Maximum Likelihood Estimator for estimating the parameter shape of the generalized gaussian noise in the class of causal time series. Monte Carlo experiments confirm the accuracy of the proposed estimator.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Computer Science, Interdisciplinary Applications
Takumi Uemoto, Kanta Naito
Summary: This study introduces a support vector regression method with penalized likelihood, incorporating the ε-insensitive loss function into the likelihood and combining it with the penalty for regression coefficients. Monte Carlo simulations confirm the effectiveness of the proposed method, with results reported on real data sets.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2022)
Article
Economics
Francisco Blasques, Janneke van Brummelen, Siem Jan Koopman, Andre Lucas
Summary: The article discusses the maximum likelihood estimator for stochastic time-varying parameter models, focusing on global identification, invertibility, strong consistency, and asymptotic normality of the model. A detailed illustration is provided for a conditional volatility model.
JOURNAL OF ECONOMETRICS
(2022)
Article
Statistics & Probability
Meng Xu, Qiuping Wang
Summary: The proposed network Poisson model is used for simulating weighted directed networks, taking into account the sparsity, degree heterogeneity, and homophily caused by node covariates. The research shows that, as the number of nodes approaches infinity, the maximum likelihood estimators can achieve a certain level of accuracy.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Mathematics
Juan R. A. Bobenrieth, Eugenio S. A. Bobenrieth, Andres F. Villegas, Brian D. Wright
Summary: This paper introduces three key features of standard dynamic volatility models and presents a novel method for proof of consistency and asymptotic normality, laying a foundation for estimation and hypothesis testing of nonstationary models without detrending.
Article
Engineering, Electrical & Electronic
Rhythm Grover, Aditi Sharma, Theo Delcourt, Debasis Kundu
Summary: This paper introduces a computationally faster methodology for estimating parameters of a 2-D sinusoidal model in the presence of noise, which is theoretically as efficient as ordinary least squares estimators. Extensive simulation studies show that these estimators can replace least squares estimators successfully for sample sizes as small as 20 x 20 and signal-to-noise ratios as low as 12 dB.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Statistics & Probability
Suli Cheng, Jianbao Chen
Summary: This paper introduces a partially linear single-index spatial autoregressive model and proposes its profile maximum likelihood estimators. The consistency and asymptotic normality of the estimators for parameters and unknown link function are derived under certain regular conditions. Monte Carlo simulations are used to evaluate the performance of these estimators in finite sample cases, and the method is applied to a real data set of Boston Housing Price for illustration.
STATISTICAL PAPERS
(2021)
Article
Mathematics
Jianbao Chen, Suli Cheng
Summary: This article introduces a partially linear additive spatial error model (PLASEM) specification and its corresponding generalized method of moments (GMM), deriving consistency and asymptotic normality of estimators for cases with nonparametric terms. The finite sample performance of estimates is assessed through Monte Carlo simulations, and the proposed method is illustrated through the analysis of Boston housing data.
Article
Engineering, Electrical & Electronic
Anjali Mittal, Rhythm Grover, Debasis Kundu, Amit Mitra
Summary: In this paper, two computationally efficient algorithms are proposed to estimate the parameters of the elementary chirp model, based on two different initial estimators. The proposed estimators are consistent and have the same asymptotic distribution as the least squares estimators, with lower computational intensity. Sequential efficient procedures are also proposed to estimate the parameters of the multi-component elementary chirp model, with asymptotic properties coinciding with the least squares estimators. The importance of these efficient algorithms lies in their ability to produce efficient frequency rate estimators in a fixed number of iterations and achieve Cramer-Rao lower bounds asymptotically.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Mathematics
Abdelouahab Bibi, Fateh Merahi
Summary: This paper studies the probabilistic and statistical properties of a continuous-time version of bilinear processes driven by a standard Brownian motion in the frequency domain. The structure and covariance function of the process are examined, leading to the analysis of the strong consistency and asymptotic normality of Whittle estimates for unknown parameters. Additionally, finite sample properties are explored through Monte Carlo experiments, with the model ultimately applied to modeling currency exchange rates.
COMMUNICATIONS IN MATHEMATICS AND STATISTICS
(2021)
Article
Engineering, Civil
I. Ben Nasr, F. Chebana
Summary: Hydrological extreme events are composed of several correlated variables, and the dependence structure between these variables needs to be considered for better risk assessment using copulas. Mixture copula is suitable for extreme events generated from different phenomena, but existing parameter estimation methods for mixture copula have drawbacks. To overcome these drawbacks, a new parameter estimation approach based on the maximum pseudo-likelihood using a metaheuristic algorithm is proposed. Simulation and real data studies show that the proposed method can estimate parameters accurately even with small sample sizes compared to existing methods.
JOURNAL OF HYDROLOGY
(2022)
Article
Statistics & Probability
Alpha Oumar Diallo, Aliou Diop, Jean-Francois Dupuy
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2017)
Article
Parasitology
Cheikh Talla, Diawo Diallo, Ibrahima Dia, Yamar Ba, Jacques-Andre Ndione, Andrew P. Morse, Aliou Diop, Mawlouth Diallo
PARASITES & VECTORS
(2016)
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Soil Science
Mariama Dalanda Diallo, Stephen A. Wood, Aly Diallo, Minda Mahatma-Saleh, Ousmane Ndiaye, Alfred Kouly Tine, Thierno Ngamb, Mamadou Guisse, Seynabou Seck, Aliou Diop, Aliou Guisse
SOIL & TILLAGE RESEARCH
(2016)
Article
Statistics & Probability
Aba Diop, Aliou Diop, Jean-Francois Dupuy
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2016)
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Computer Science, Interdisciplinary Applications
Pathe Ndao, Aliou Diop, Jean-Francois Dupuy
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2014)
Article
Parasitology
Maryam Diarra, Moussa Fall, Assane G. Fall, Aliou Diop, Momar Talla Seck, Claire Garros, Thomas Balenghien, Xavier Allene, Ignace Rakotoarivony, Renaud Lancelot, Iba Mall, Mame Thierno Bakhoum, Ange Michel Dosum, Massouka Ndao, Jeremy Bouyer, Helene Guis
PARASITES & VECTORS
(2014)
Article
Multidisciplinary Sciences
Cheikh Loucoubar, Richard Paul, Avner Bar-Hen, Augustin Huret, Adama Tall, Cheikh Sokhna, Jean-Francois Trape, Alioune Badara Ly, Joseph Faye, Abdoulaye Badiane, Gaoussou Diakhaby, Fatoumata Diene Sarr, Aliou Diop, Anavaj Sakuntabhai, Jean-Francois Bureau
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Multidisciplinary Sciences
Cheikh Loucoubar, Bronner Goncalves, Adama Tall, Cheikh Sokhna, Jean-Francois Trape, Fatoumata Diene Sarr, Joseph Faye, Abdoulaye Badiane, Alioune Badara Ly, Aliou Diop, Avner Bar-Hen, Jean-Francois Bureau, Anavaj Sakuntabhai, Richard Paul
Article
Multidisciplinary Sciences
Cheikh Ndour, Simplice Dossou Gbete, Noelle Bru, Michal Abrahamowicz, Arnaud Fauconnier, Mamadou Traore, Aliou Diop, Pierre Fournier, Alexandre Dumont
Article
Multidisciplinary Sciences
Cheikh Talla, Diawo Diallo, Ibrahima Dia, Yamar Ba, Jacques-Andre Ndione, Amadou Alpha Sall, Andy Morse, Aliou Diop, Mawlouth Diallo
Article
Multidisciplinary Sciences
Maryam Diarra, Moussa Fall, Renaud Lancelot, Aliou Diop, Assane G. Fall, Ahmadou Dicko, Momar Talla Seck, Claire Garros, Xavier Allene, Ignace Rakotoarivony, Mame Thierno Bakhoum, Jeremy Bouyer, Helene Guis
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Statistics & Probability
Sophie Dabo-Niang, Sidi Ali Ould-Abdi, Ahmedoune Ould-Abdi, Aliou Diop
STATISTICAL METHODS AND APPLICATIONS
(2014)
Article
Statistics & Probability
Mamadou Lamine Diop, Aliou Diop, Abdou Ka Diongue
REVSTAT-STATISTICAL JOURNAL
(2016)
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Statistics & Probability
Mor Ndongo, Abdou Ka Diongue, Aliou Diop, Simplice Dossou-Gbete
Article
Statistics & Probability
M. A. Niang, G. M. Nkiet, A. Diop
MATHEMATICAL METHODS OF STATISTICS
(2012)