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Littérature scientifique sur le sujet « M-quantile »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "M-quantile"

Borgoni, Riccardo, Paola Del Bianco, Nicola Salvati, Timo Schmid, and Nikos Tzavidis. "Modelling the distribution of health-related quality of life of advanced melanoma patients in a longitudinal multi-centre clinical trial using M-quantile random effects regression." Statistical Methods in Medical Research 27, no. 2 (2016): 549–63. http://dx.doi.org/10.1177/0962280216636651.

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Health-related quality of life assessment is important in the clinical evaluation of patients with metastatic disease that may offer useful information in understanding the clinical effectiveness of a treatment. To assess if a set of explicative variables impacts on the health-related quality of life, regression models are routinely adopted. However, the interest of researchers may be focussed on modelling other parts (e.g. quantiles) of this conditional distribution. In this paper, we present an approach based on quantile and M-quantile regression to achieve this goal. We applied the methodol

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Alfò, Marco, Nicola Salvati, and M. Giovanna Ranallli. "Finite mixtures of quantile and M-quantile regression models." Statistics and Computing 27, no. 2 (2016): 547–70. http://dx.doi.org/10.1007/s11222-016-9638-1.

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Komunjer, Ivana, and Quang Vuong. "SEMIPARAMETRIC EFFICIENCY BOUND IN TIME-SERIES MODELS FOR CONDITIONAL QUANTILES." Econometric Theory 26, no. 2 (2009): 383–405. http://dx.doi.org/10.1017/s0266466609100038.

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We derive the semiparametric efficiency bound in dynamic models of conditional quantiles under a sole strong mixing assumption. We also provide an expression of Stein’s (1956) least favorable parametric submodel. Our approach is as follows: First, we construct a fully parametric submodel of the semiparametric model defined by the conditional quantile restriction that contains the data generating process. We then compare the asymptotic covariance matrix of the MLE obtained in this submodel with those of the M-estimators for the conditional quantile parameter that are consistent and asymptotical

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Otto-Sobotka, Fabian, Nicola Salvati, Maria Giovanna Ranalli, and Thomas Kneib. "Adaptive semiparametric M-quantile regression." Econometrics and Statistics 11 (July 2019): 116–29. http://dx.doi.org/10.1016/j.ecosta.2019.03.001.

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Maiboroda, Rostyslav, Vitaliy Miroshnychenko, and Olena Sugakova. "Quantile estimators for regression errors in mixture models with varying concentrations." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 1 (2024): 45–50. http://dx.doi.org/10.17721/1812-5409.2024/1.8.

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In this paper we consider data obtained from a mixture of M different sub-populations (mixture components). Dependencies between the observed variables are described by nonlinear regression models with unknown regression parameters and error terms distributions different for different components. The mixing probabilities (concentrations of the components in the mixture) vary from observation to observation. Estimators for quantiles of error terms distributions are considered based on weighted empirical distribution functions of the regression models residuals. Consistency of these estimators i

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Moreno, Justo De Jorge, and Oscar Rojas Carrasco. "EVOLUTION OF EFFICIENCY AND ITS DETERMINANTS IN THE RETAIL SECTOR IN SPAIN: NEW EVIDENCE." Journal of Business Economics and Management 16, no. 1 (2014): 244–60. http://dx.doi.org/10.3846/16111699.2012.732958.

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The purpose of this work is twofold: on the one hand, recent methodologies will be used to estimate technical efficiency and its determinants factors in Spain's retail sector. In particular, the order-m approach, which is based on the concept of expected minimum input function and quantile regression, for the analysis of the factors determinants of efficiency is used. On the other hand, the results obtained applying the methods mentioned in the Spanish retail sector can contribute to opening up a new field of analysis since the results may be compared by means of the methodologies proposed as

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Nulkarim, Aldi Rochman, and Ika Yuni Wulansari. "M-quantile Chambers-Dunstan Untuk Pendugaan Area Kecil." Seminar Nasional Official Statistics 2021, no. 1 (2021): 80–89. http://dx.doi.org/10.34123/semnasoffstat.v2021i1.1065.

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Metode Small Area Estimations (SAE) digunakan sebagai pendekatan yang reliabel dalam mengatasi kendala ketidakcukupan sampel pada survei sampel. BPS memproduksi statistik area kecil menggunakan metode SAE popular seperti Empirical Best Linear Unbiased Prediction dalam model Fay-Herriot (EBLUP-FH). Metode EBLUP-FH sebagai pendekatan parametrik memerlukan asumsi normalitas dan terbebas dari outliers pada kedua komponen random effect-nya. Namun, hal tersebut sulit dipenuhi karena seringkali data di lapangan berperilaku ekstrim. Metode SAE M-quantile Chambers-Dunstan (CD) merelaksasi asumsi parame

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Al-Sabri, Haithm Mohammed Hamood, Norhafiza Nordin, and Hanita Kadir Shahar. "The impact of chief executive officer (CEO) and deal characteristics on mergers and acquisitions (M&A) duration: A quantile regression evidence from an emerging market." Asian Academy of Management Journal of Accounting and Finance 18, no. 1 (2022): 101–32. http://dx.doi.org/10.21315/aamjaf2022.18.1.5.

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This paper examines the impact of chief executive officer (CEO) and deal characteristics on mergers and acquisitions (M&A) duration in Malaysia. Univariate analysis and quantile regression (QR) are performed on 556 completed M&As transactions undertaken by Malaysian public firms from 2001 to 2019. In line with the upper echelons theory, which states that organizational outcomes can be predicted by looking at the characteristics of top-level executives, the findings from QR show that CEO characteristics significantly affect acquisition duration. This effect is conditional on the duratio

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Dreassi, Emanuela, M. Giovanna Ranalli, and Nicola Salvati. "Semiparametric M-quantile regression for count data." Statistical Methods in Medical Research 23, no. 6 (2014): 591–610. http://dx.doi.org/10.1177/0962280214536636.

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A.A.Aly, Eman-Eldin. "On quantile processes for m-dependent Rv's." Statistics 18, no. 3 (1987): 423–35. http://dx.doi.org/10.1080/02331888708802039.

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Thèses sur le sujet "M-quantile"

CARCAGNÌ, ANTONELLA. "Una specificazione semiparametrica del modello di regressione M-Quantile ad effetti casuali con applicazioni a dati ambientali georeferenziati." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/180711.

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Abstract Questo lavoro di tesi ha come finalità lo sviluppo e l’implementazione di un modello semiparametrico M-quantile ad effetti random che sia in grado di cogliere l’eventuale presenza di un trend spaziale nei dati ambientali. Il modello proposto è una estensione del modello M-quantile ad effetti casuali di base in cui è stata inclusa una componente spaziale. La componente spaziale è modellata combinando insieme un’intercetta random (Chambers e Tzavidis, 2006) che coglie l’effetto del gruppo e un termine semiparametrico per catturare la regolarità residua nello spazio (Pratesi et al.

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Meneghel, Danilevicz Ian. "Robust linear mixed models, alternative methods to quantile regression for panel data, and adaptive LASSO quantile regression with fixed effects." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST176.

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La thèse est constituée de trois chapitres. Le premier s'intéresse au lien entre l’exposition à la pollution de l’air et les affections respiratoires chez les enfants et les adolescents. La cohorte comprend 82 individus observés mensuellement pendant 6 mois. Nous proposons un modèle linéaire mixte robuste combiné à une analyse en composantes principales afin de gérer la multicolinéarité entre les covariables et l’impact des observations extrêmes sur les estimations. Le deuxième chapitre analyse des données de panel au moyen de modèles à effets fixes et utilisant différentes fonction de perte.

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Chao, Shih-Kang. "Quantile regression in risk calibration." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17223.

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Die Quantilsregression untersucht die Quantilfunktion QY |X (τ ), sodass ∀τ ∈ (0, 1), FY |X [QY |X (τ )] = τ erfu ̈llt ist, wobei FY |X die bedingte Verteilungsfunktion von Y gegeben X ist. Die Quantilsregression ermo ̈glicht eine genauere Betrachtung der bedingten Verteilung u ̈ber die bedingten Momente hinaus. Diese Technik ist in vielerlei Hinsicht nu ̈tzlich: beispielsweise fu ̈r das Risikomaß Value-at-Risk (VaR), welches nach dem Basler Akkord (2011) von allen Banken angegeben werden muss, fu ̈r ”Quantil treatment-effects” und die ”bedingte stochastische Dominanz (CSD)”, welches wirtschaf

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Sabbah, Camille. "Contribution à l'étude des M-estimateurs polynômes locaux." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2010. http://tel.archives-ouvertes.fr/tel-00509898.

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L'objet de cette thèse est d'établir des résultats asymptotiques pour l'estimateur du quantile conditionnel par la méthode des polynômes locaux ainsi qu'à la généralisation de ces résultats pour les M-estimateurs. Nous étudions ces estimateurs et plus particulièrement leur représentation de Bahadur et leur biais. Nous donnons en outre un résultat sur les intervalles de confiance uniformes construits à partir de cette représentation pour le quantile conditionnel et ses dérivées.

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Bassene, Aladji. "Contribution à la modélisation spatiale des événements extrêmes." Thesis, Lille 3, 2016. http://www.theses.fr/2016LIL30039/document.

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Dans cette de thèse, nous nous intéressons à la modélisation non paramétrique de données extrêmes spatiales. Nos résultats sont basés sur un cadre principal de la théorie des valeurs extrêmes, permettant ainsi d’englober les lois de type Pareto. Ce cadre permet aujourd’hui d’étendre l’étude des événements extrêmes au cas spatial à condition que les propriétés asymptotiques des estimateurs étudiés vérifient les conditions classiques de la Théorie des Valeurs Extrêmes (TVE) en plus des conditions locales sur la structure des données proprement dites. Dans la littérature, il existe un vaste panor

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SABBI, ALBERTO. "Mixed effect quantile and M-quantile regression for spatial data." Doctoral thesis, 2020. http://hdl.handle.net/11573/1456341.

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Observed data are frequently characterized by a spatial dependence; that is the observed values can be influenced by the "geographical" position. In such a context it is possible to assume that the values observed in a given area are similar to those recorded in neighboring areas. Such data is frequently referred to as spatial data and they are frequently met in epidemiological, environmental and social studies, for a discussion see Haining, (1990). Spatial data can be multilevel, with samples being composed of lower level units (population, buildings) nested within higher level units (census

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MERLO, LUCA. "On quantile regression models for multivariate data." Doctoral thesis, 2022. http://hdl.handle.net/11573/1613037.

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The goal of this thesis is to bridge the gap between univariate and multivariate quantiles by extending the study of univariate quantile regression and its generalizations to multivariate responses. The statistical analysis focuses on a multivariate framework where we consider vector-valued quantile functions associated with multivariate distributions, providing inferential procedures and establishing the asymptotic properties of the proposed estimators. We illustrate their applicability in a wide variety of scientific settings, including time series, longitudinal and clustered data. The disse

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Chapitres de livres sur le sujet "M-quantile"

Borgoni, Riccardo, Enrico Fabrizi, Nicola Salvati, Francesco Schirripa Spagnolo, and Diego Zappa. "Partial M-Quantile Regression for Predictive Mantainance." In Italian Statistical Society Series on Advances in Statistics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-64431-3_42.

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Bianchi, Annamaria. "M-Quantile Small Area Estimation for Panel Data." In Topics in Theoretical and Applied Statistics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27274-0_11.

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Pratesi, Monica. "M-Quantile Small Area Models for Measuring Poverty at a Local Level." In Contributions to Statistics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05320-2_2.

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Koltchinskii, V. "M-Estimation and Spatial Quantiles." In Robust Statistics, Data Analysis, and Computer Intensive Methods. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2380-1_16.

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Kokic, Philip, Jens Breckling, and Oliver Lübke. "A New Definition of Multivariate M-quantiles." In Statistical Data Analysis Based on the L1-Norm and Related Methods. Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8201-9_2.

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Elsner, James B., and Thomas H. Jagger. "Intensity Models." In Hurricane Climatology. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199827633.003.0012.

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Strong hurricanes, such as Camille in 1969, Andrew in 1992, and Katrina in 2005, cause catastrophic damage. It is important to have an estimate of when the next big one will occur. You also want to know what influences the strongest hurricanes and whether they are getting stronger as the earth warms. This chapter shows you how to model hurricane intensity. The data are basinwide lifetime highest intensities for individual tropical cyclones over the North Atlantic and county-level hurricane wind intervals. We begin by considering trends using the method of quantile regression and then examine e

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Ahmad, Ishfaq, Alam Zeb Khan, Mirza Barjees Baig, and Ibrahim M. Almanjahie. "Flood Frequency Analysis Using Bayesian Paradigm." In Advances in Environmental Engineering and Green Technologies. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9771-1.ch005.

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At-site flood frequency analysis (FFA) of extreme hydrological events under Bayesian paradigm has been carried out and compared with frequentist paradigm of maximum likelihood estimation (MLE). The main objective of this chapter is to identify the best approach between Bayesian and frequentist one for at-site FFA. As a case study, the data of only two stations were used, Kotri and Rasul, and Bayesian and MLE approaches were implemented. Most commonly used tests were applied for checking initial assumptions. Goodness of fit (GOF) tests were used to identify the best model, which indicated that

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"Asymptotics of the Perturbed Sample Quantile for a Sequence of m—dependent Stationary Random Process." In Statistical Sciences and Data Analysis. De Gruyter, 1993. http://dx.doi.org/10.1515/9783112318867-040.

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Gao, Hongyuan, Yangyang Hou, Shibo Zhang, and Ming Diao. "An Efficient Approximation for Nakagami-m Quantile Function Based on Generalized Opposition-Based Quantum Salp Swarm Algorithm." In Prime Archives in Applied Mathematics. Vide Leaf, Hyderabad, 2021. http://dx.doi.org/10.37247/paam2ed.2.2021.21.

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Mitchell, James, Aubrey Poon, and Gian Luigi Mazzi. "Nowcasting Euro Area GDP Growth Using Bayesian Quantile Regression." In Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling. Emerald Publishing Limited, 2022. http://dx.doi.org/10.1108/s0731-90532021000043a004.

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Actes de conférences sur le sujet "M-quantile"

Girinoto, Kusman Sadik, and Indahwati. "Robust small area estimation of poverty indicators using M-quantile approach (Case study: Sub-district level in Bogor district)." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979448.

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Hohnecker, K. H. "OPTIMAL TWO-STAGE BAYESIAN DESIGN FOR PENETRATION LIMIT VELOCITY TESTING." In 34th International Symposium on Ballistics. Destech Publications, Inc., 2025. https://doi.org/10.12783/ballistics25/37231.

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Quantile estimation (QE), also called sensitivity testing, is used in many fields of study. Ballistic performance metrics known as limit velocities (V50, V90, etc.) are estimated via QE. A popular QE method for finding said limit velocities is logistic regression. To perform the regression, the experimentalist must determine a set of test impact velocities, known as the experiment’s “design”. Many of the leading design methods used in small arms limit velocity tests are “sequential” in that the mth test velocity is determined by the previous m − 1 test results. Although these designs are typic

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Lucas, Cla´udia, G. Muraleedharan, and C. Guedes Soares. "Application of Regional Frequency Analysis for Identification of Homogeneous Regions of Design Wave Conditions Offshore Portugal." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-50214.

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Regional frequency analysis (RFA) based on L-moments is applied to the HIPOCAS hindcast data using daily maximum significant wave heights offshore Portugal to identify the homogeneous regions and to suggest the appropriate regional frequency distribution and extreme quantiles. Several statistics are computed at the various grid points in the area of study to classify the wave conditions of the regions. The daily maximum significant wave heights of the rough winter month January are used for this case study. The results of the study have shown that there are 3 homogeneous regions in the offshor

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Sidenko, Vladyslav, and Dmytro Oshurok. "Future temperature and precipitation climate indices changes over the Transcarpathia region on EURO-CORDEX multimodel ensemble." In International Conference of Young Scientists on Meteorology, Hydrology and Environmental Monitoring. Ukrainian Hydrometeorological Institute, 2023. http://dx.doi.org/10.15407/icys-mhem.2023.025.

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This study aims to assess potential climate changes in the Transcarpathia Region in the period 2021-2050 relative to the 1991-2020 base period based on the calculation of temperature and precipitation climate indices: annual average air temperature, number of frost days (FD), number of summer days (SU), number of tropical days (TD), amount of winter precipitation, amount of summer precipitation, annual count of days with more than 20 mm precipitation (R20mm) and maximum amount of precipitation for two consecutive days (AMP2). The domain under study includes the Transcarpathia Region of Ukraine

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Rapports d'organisations sur le sujet "M-quantile"

Cattaneo, Matias D., Richard K. Crump, Max H. Farrell, and Yingjie Feng. Nonlinear Binscatter Methods. Federal Reserve Bank of New York, 2024. http://dx.doi.org/10.59576/sr.1110.

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Binned scatter plots are a powerful statistical tool for empirical work in the social, behavioral, and biomedical sciences. Available methods rely on a quantile-based partitioning estimator of the conditional mean regression function to primarily construct flexible yet interpretable visualization methods, but they can also be used to estimate treatment effects, assess uncertainty, and test substantive domain-specific hypotheses. This paper introduces novel binscatter methods based on nonlinear, possibly nonsmooth M-estimation methods, covering generalized linear, robust, and quantile regressio

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