Skip to content
naulon
Not checkedNot checked for notices yet.

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

Marco Geraci

Journal of Statistical Software · 2014

doi:10.18637/jss.v057.i13 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Inference in quantile analysis has received considerable attention in the recent years. Linear quantile mixed models (Geraci and Bottai 2014) represent a ?exible 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 e?ects 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.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.