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Rachid El Halimi

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Articles

Estimation Approach for a Linear Quantile-Regression Model with Long-Memory Stationary GARMA Errors

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By Oumaima Essefiani, Rachid El Halimi, El Halimi
| MDPI
1. Introduction Linear regression is one of the most common and well understood techniques for modeling the relationship between one or more covariates or predictor variables, X, and the conditional mean E ( Y | X = x ) of the response variable Y, given X = x . The conditional mean minimizes the expected squared error: E ( Y | X = x ) = a r g m i n μ E [ ( Y − μ ) 2 | X = x ] .
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Some Estimation Methods for a Random Coefficient in the Gegenbauer Autoregressive Moving-Average Model

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By Rachid El Halimi, El Halimi, Oumaima Essefiani
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Sustainability | Free Full-Text | Predicting the Production and Depletion of Rare Earth Elements and Their Influence on Energy Sector Sustainability through the Utilization of Multilevel Linear Prediction Mixed-Effects Models with R Software

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By El Khalil Cherif, El Mustapha Azzirgue, Rachid El Halimi, Yassine Ou Larbi
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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