A gradient search maximization algorithm for the asymmetric Laplace likelihood

DOI10.1080/00949655.2014.908879zbMath1457.62014OpenAlexW2018964583MaRDI QIDQ5220837

Nicola Orsini, Marco Geraci, Matteo Bottai

Publication date: 27 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://discovery.ucl.ac.uk/id/eprint/1424872/

zbMATH Keywords

quantile regressionasymmetric Laplace distributiondirect search optimization algorithmsLaplace regressionmixed-effects quantile regression

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

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Uses Software

• Stata
• lqmm
• laplace

Cites Work

• Linear quantile mixed models
• Quantile regression for longitudinal data based on latent Markov subject-specific parameters
• The Gaussian hare and the Laplacian tortoise: computability of squared-error versus absolute-error estimators. With comments by Ronald A. Thisted and M. R. Osborne and a rejoinder by the authors
• Laplace regression with censored data
• Quantile regression for longitudinal data using the asymmetric Laplace distribution
• Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data
• Regression Quantiles
• Goodness of Fit and Related Inference Processes for Quantile Regression

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