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Details about Marco Geraci

Workplace:Dipartimento di Metodi e modelli per l'economia, il territorio e la finanza (MEMOTEF) (Department of Methods and Models for Economics, Territory and Finance), Facoltà di Economia (Faculty of Economics), "Sapienza" Università di Roma (Sapienza University of Rome), (more information at EDIRC)

Access statistics for papers by Marco Geraci.

Last updated 2024-01-09. Update your information in the RePEc Author Service.

Short-id: pge379


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Journal Articles

2022

  1. Alessio Farcomeni and Marco Geraci's contribution to the ‘First Discussion Meeting on Statistical Aspects of the Covid‐19 Pandemic’
    Journal of the Royal Statistical Society Series A, 2022, 185, (4), 1829-1830 Downloads

2019

  1. Additive quantile regression for clustered data with an application to children's physical activity
    Journal of the Royal Statistical Society Series C, 2019, 68, (4), 1071-1089 Downloads
  2. Modelling and estimation of nonlinear quantile regression with clustered data
    Computational Statistics & Data Analysis, 2019, 136, (C), 30-46 Downloads View citations (4)

2018

  1. Multiple Imputation for Bounded Variables
    Psychometrika, 2018, 83, (4), 919-940 Downloads View citations (1)

2017

  1. Using functional data analysis to understand daily activity levels and patterns in primary school-aged children: Cross-sectional analysis of a UK-wide study
    PLOS ONE, 2017, 12, (11), 1-17 Downloads View citations (2)

2016

  1. Aranda-Ordaz quantile regression for student performance assessment
    Journal of Applied Statistics, 2016, 43, (1), 58-71 Downloads View citations (5)
  2. Probabilistic principal component analysis to identify profiles of physical activity behaviours in the presence of non-ignorable missing data
    Journal of the Royal Statistical Society Series C, 2016, 65, (1), 51-75 Downloads View citations (2)

2014

  1. Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression
    Journal of Statistical Software, 2014, 057, (i13) Downloads View citations (16)
  2. Quality Control Methods in Accelerometer Data Processing: Identifying Extreme Counts
    PLOS ONE, 2014, 9, (1), 1-6 Downloads

2013

  1. Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time
    PLOS ONE, 2013, 8, (6), 1-8 Downloads View citations (1)

2011

  1. Where do Italian universities stand? An in-depth statistical analysis of national and international rankings
    Scientometrics, 2011, 87, (3), 667-681 Downloads View citations (5)
 
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