In the present work we generalize the univariate M-quantile regression to the analysis of multivariate dependent outcomes. Extending the notion of directional quantiles, we introduce directional M-quantiles which are obtained as projections of the original data on a specified unit norm direction. In order to take into consideration the correlation within grouped measurements and to increase efficiency, we develop a marginal M-Quantile regression model extending the well known generalized estimating equations approach. We build M-quantile regions and contours which allow us to investigate the effect of the covariates on the location, spread and shape of the distribution of the responses. To identify potential outliers and provide a simple visual representation of the variability of the M quantile contours estimator, we construct confidence envelope via nonparametric bootstrap. The validity of our method is analyzed through the study of the wages data from the National Longitudinal Survey of Youth.

Directional M-quantile regression for multivariate dependent outcomes

Merlo, Luca
;
2021-01-01

Abstract

In the present work we generalize the univariate M-quantile regression to the analysis of multivariate dependent outcomes. Extending the notion of directional quantiles, we introduce directional M-quantiles which are obtained as projections of the original data on a specified unit norm direction. In order to take into consideration the correlation within grouped measurements and to increase efficiency, we develop a marginal M-Quantile regression model extending the well known generalized estimating equations approach. We build M-quantile regions and contours which allow us to investigate the effect of the covariates on the location, spread and shape of the distribution of the responses. To identify potential outliers and provide a simple visual representation of the variability of the M quantile contours estimator, we construct confidence envelope via nonparametric bootstrap. The validity of our method is analyzed through the study of the wages data from the National Longitudinal Survey of Youth.
2021
9788891927361
Correlated data
GMQEE
Marginal approach
M-quantile contours
File in questo prodotto:
File Dimensione Formato  
Merlo_Directional-M-quantile-regression_2021.pdf

non disponibili

Licenza: Creative commons
Dimensione 357.39 kB
Formato Adobe PDF
357.39 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14092/3593
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact