activity
20182022
most citedA Review of Latent Space Models for Social Networks

4 citations · 7 across the 7 of their papers we have counts for

collaborators

9 papers

stat.ME2022

Operationalizing Legislative Bodies: A Methodological and Empirical Perspective

Carolina Luque, Juan Sosa

This manuscript extensively reviews applications, extensions, and models derived from the Bayesian ideal point estimator. We primarily focus our attention on studies conducted in t…

stat.AP2022

Bayesian modeling of the political preferences of the Colombian Senate 2006-2010: electoral behavior and parapolitics

Juan Valero, Juan Sosa, Carolina Luque

In this paper, a Bayesian spatial voting model is applied for the first time to characterize the legislative behavior of the Senate of the Republic of Colombia for the period 2006-…

stat.AP2022

Small area estimation using multiple imputation in three-parameter logistic models

Cristian Tellez-Piñerez, Leonardo Trujillo, Andrés Gutiérrez-Rojas +1

We propose a novel methodology relating item response theory methods with small area estimation strategies in the presence of missing data. Specifically, we propose an unbiased est…

stat.ME20212 cited

A Gentle Introduction to Bayesian Hierarchical Linear Regression Models

Juan Sosa, Jeimy Aristizabal

Considering the flexibility and applicability of Bayesian modeling, in this work we revise the main characteristics of two hierarchical models in a regression setting. We study the…

stat.ME2021

Time-Varying Coefficient Model Estimation Through Radial Basis Functions

Juan Sosa, Lina Buitrago

In this paper we estimate the dynamic parameters of a time-varying coefficient model through radial kernel functions in the context of a longitudinal study. Our proposal is based o…

cs.SI20211 cited

A Latent Space Model for Multilayer Network Data

Juan Sosa, Brenda Betancourt

In this work, we propose a Bayesian statistical model to simultaneously characterize two or more social networks defined over a common set of actors. The key feature of the model i…