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

Marco Geraci

Journal of Statistical Software, 2014, vol. 057, issue i13

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: 2014-05-06
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:057:i13

DOI: 10.18637/jss.v057.i13

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