Mohamed Chaouch

654 total citations
11 papers, 95 citations indexed

About

Mohamed Chaouch is a scholar working on Statistics and Probability, Artificial Intelligence and Finance. According to data from OpenAlex, Mohamed Chaouch has authored 11 papers receiving a total of 95 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 4 papers in Artificial Intelligence and 2 papers in Finance. Recurrent topics in Mohamed Chaouch's work include Statistical Methods and Inference (7 papers), Advanced Statistical Methods and Models (6 papers) and Bayesian Methods and Mixture Models (4 papers). Mohamed Chaouch is often cited by papers focused on Statistical Methods and Inference (7 papers), Advanced Statistical Methods and Models (6 papers) and Bayesian Methods and Mixture Models (4 papers). Mohamed Chaouch collaborates with scholars based in France, United Arab Emirates and Tunisia. Mohamed Chaouch's co-authors include Hervé Cardot, Ali Gannoun, Jérôme Saracco, Christian de Peretti, Abdelwahed Trabelsi, Jaonary Rabarisoa, Thierry Château, Céline Teulière and Florian Chabot and has published in prestigious journals such as Annals of Operations Research, Computational Statistics & Data Analysis and Journal of Multivariate Analysis.

In The Last Decade

Mohamed Chaouch

11 papers receiving 92 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mohamed Chaouch France	6	64	32	18	16	14	11	95
Rainer Dyckerhoff Germany	8	118 1.8×	21 0.7×	9 0.5×	38 2.4×	67 4.8×	13	175
Okechukwu J. Obulezi Nigeria	10	215 3.4×	60 1.9×	26 1.4×	44 2.8×	58 4.1×	40	229
Vivekananda Roy United States	10	181 2.8×	111 3.5×	5 0.3×	9 0.6×	9 0.6×	30	224
Feng‐Chang Xie China	11	274 4.3×	83 2.6×	15 0.8×	31 1.9×	55 3.9×	20	309
Sanying Feng China	11	237 3.7×	36 1.1×	26 1.4×	20 1.3×	9 0.6×	36	290
Julián de la Horra Spain	7	73 1.1×	18 0.6×	7 0.4×	23 1.4×	25 1.8×	27	100
Edward L. Melnick United States	6	22 0.3×	9 0.3×	8 0.4×	17 1.1×	11 0.8×	16	73
Guillermo Martínez‐Flórez Colombia	10	274 4.3×	93 2.9×	33 1.8×	23 1.4×	122 8.7×	61	308
C. Satheesh Kumar India	10	268 4.2×	117 3.7×	43 2.4×	36 2.3×	98 7.0×	69	293
Daniel Cunha United States	4	179 2.8×	24 0.8×	26 1.4×	17 1.1×	114 8.1×	7	202

Countries citing papers authored by Mohamed Chaouch

Since Specialization

Citations

This map shows the geographic impact of Mohamed Chaouch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mohamed Chaouch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Chaouch more than expected).

Fields of papers citing papers by Mohamed Chaouch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohamed Chaouch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mohamed Chaouch. The network helps show where Mohamed Chaouch may publish in the future.

Co-authorship network of co-authors of Mohamed Chaouch

This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Chaouch. A scholar is included among the top collaborators of Mohamed Chaouch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohamed Chaouch. Mohamed Chaouch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Chaouch, Mohamed, et al.. (2019). Optimal asymptotic MSE of kernel regression estimate for continuous time processes with missing at random response. Statistics & Probability Letters. 154. 108532–108532. 2 indexed citations

Chaouch, Mohamed. (2018). Volatility estimation in a nonlinear heteroscedastic functional regression model with martingale difference errors. Journal of Multivariate Analysis. 170. 129–148. 4 indexed citations

Chabot, Florian, Mohamed Chaouch, Jaonary Rabarisoa, Céline Teulière, & Thierry Château. (2016). Accurate 3D car pose estimation. HAL (Le Centre pour la Communication Scientifique Directe). 3807–3811. 2 indexed citations

Chaouch, Mohamed, et al.. (2016). Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier. Annals of Operations Research. 262(2). 653–681. 11 indexed citations

Chaouch, Mohamed, et al.. (2016). NonparametricM-estimation for right censored regression model with stationary ergodic data. Statistical Methodology. 33. 234–255. 5 indexed citations

Chaouch, Mohamed, et al.. (2016). Rate of uniform consistency for a class of mode regression on functional stationary ergodic data. Statistical Methods & Applications. 26(1). 19–47. 9 indexed citations

Chaouch, Mohamed, et al.. (2014). Vector-on-function quantile regression for stationary ergodic processes. Journal of the Korean Statistical Society. 44(2). 161–178. 1 indexed citations

Chaouch, Mohamed, et al.. (2014). Randomly censored quantile regression estimation using functional stationary ergodic data. Journal of nonparametric statistics. 27(1). 65–87. 24 indexed citations

Chaouch, Mohamed, et al.. (2010). Design-based estimation for geometric quantiles with application to outlier detection. Computational Statistics & Data Analysis. 54(10). 2214–2229. 10 indexed citations

10.

Chaouch, Mohamed, Ali Gannoun, & Jérôme Saracco. (2009). Estimation de quantiles géométriques conditionnels et non conditionnels. French digital mathematics library (Numdam). 150(2). 1–27. 5 indexed citations

11.

Cardot, Hervé, et al.. (2009). Properties of design-based functional principal components analysis. Journal of Statistical Planning and Inference. 140(1). 75–91. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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