Migration and students' performance: detecting geographical differences following a curves clustering approach

DOI10.1080/02664763.2020.1845624OpenAlexW3101879705MaRDI QIDQ5085679

Giada Adelfio, Gianluca Sottile, Giovanni Boscaino

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1845624

zbMATH Keywords

quantile regressioncensored and truncated datastudents' performanceclustering of curves

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Applications of statistics (62Pxx)

Uses Software

• qrcm
• clustEff

Cites Work

• Unnamed Item
• Clusters of effects curves in quantile regression models
• Model-based clustering of high-dimensional data: a review
• An estimating equation for censored and truncated quantile regression
• Parametric modeling of quantile regression coefficient functions
• Regression Quantiles
• Curve Registration
• Censored Regression Quantiles
• Parametric modeling of quantile regression coefficient functions with censored and truncated data
• Degree course change and student performance: a mixed-effect model approach
• A weighted quantile regression for left-truncated and right-censored data
• Quantile regression methods for left-truncated and right-censored data
• A Case Study in Exploratory Functional Data Analysis: Geometrical Features of the Internal Carotid Artery

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