Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression

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Authors Marco Geraci
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract Inference in quantile analysis has received considerable attention in the recent years. Linear quantile mixed models (Geraci and Bottai 2014) represent a flexible statistical tool to analyze data from sampling designs such as multilevel, spatial, panel or longitudinal, which induce some form of clustering. In this paper, I will show how to estimate conditional quantile functions with random effects using the R package lqmm. Modeling, estimation and inference are discussed in detail using a real data example. A thorough description of the optimization algorithms is also provided.
Date of publication 2014
Code Programming Language R
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