Quantile Peer Effect Models

Simulating and estimating peer effect models including the quantile-based specification (Houndetoungan, 2025 ), and the models with Constant Elasticity of Substitution (CES)-based social norm (Boucher et al., 2024 ).


QuantilePeer: An R package for Simulating and Estimation Quantile Peer Effect Models

Aristide Houndetoungan

Lifecycle: stable License: MIT R-CMD-check

CRAN R-universe DOI CRAN Downloads

Vignette

Overview

The QuantilePeer package implements estimation and simulation routines for the rank-dependent and quantile peer effect models introduced in Herstad et al. (2026). Replication code for all results in the paper is available in the Replication folder.

The package also includes functions to simulate and estimate the CES-based peer effect model developed by Boucher et al. (2024).

Installation

CRAN version

QuantilePeer can be directly installed from CRAN.

install.packages("QuantilePeer")

GitHub version

It may be possible that we updated the package without submitting the new version to CRAN. The latest version (but not necessary stable) of QuantilePeer can be installed from this GitHub repos.

remotes::install_github("ahoundetoungan/QuantilePeer", build_vignettes = TRUE)

Getting Started

See the vignettes for detailed examples demonstrating how to use the package.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("QuantilePeer")

1.0.1 by Aristide Houndetoungan, 6 days ago


https://github.com/ahoundetoungan/QuantilePeer


Report a bug at https://github.com/ahoundetoungan/QuantilePeer/issues


Browse source code at https://github.com/cran/QuantilePeer


Authors: Aristide Houndetoungan [cre, aut] (ORCID: , Eyo I. Herstad [aut] , Myungkou Shin [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports Rcpp, formula.tools, Matrix, MASS, ranger, xgboost, glmnet

Suggests knitr, rmarkdown, PartialNetwork

Linking to Rcpp, RcppArmadillo, RcppEigen, RcppNumerical, RcppProgress

System requirements: Requires the OpenMP library for parallel computing. If the OpenMP library is not available, the code is executed sequentially, and a warning is printed.


See at CRAN