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Bibliographic Details
Main Author: Levin, Ines
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.06046
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author Levin, Ines
author_facet Levin, Ines
contents Learning about the relationship between distance to landmarks and events and phenomena of interest is a multi-faceted problem, as it may require taking into account multiple dimensions, including: spatial position of landmarks, timing of events taking place over time, and attributes of occurrences and locations. Here I show that tree-based methods are well suited for the study of these questions as they allow exploring the relationship between proximity metrics and outcomes of interest in a non-parametric and data-driven manner. I illustrate the usefulness of tree-based methods vis-à-vis conventional regression methods by examining the association between: (i) distance to border crossings along the US-Mexico border and support for immigration reform, and (ii) distance to mass shootings and support for gun control.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06046
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Learning about Spatial and Temporal Proximity using Tree-Based Methods
Levin, Ines
Applications
Learning about the relationship between distance to landmarks and events and phenomena of interest is a multi-faceted problem, as it may require taking into account multiple dimensions, including: spatial position of landmarks, timing of events taking place over time, and attributes of occurrences and locations. Here I show that tree-based methods are well suited for the study of these questions as they allow exploring the relationship between proximity metrics and outcomes of interest in a non-parametric and data-driven manner. I illustrate the usefulness of tree-based methods vis-à-vis conventional regression methods by examining the association between: (i) distance to border crossings along the US-Mexico border and support for immigration reform, and (ii) distance to mass shootings and support for gun control.
title Learning about Spatial and Temporal Proximity using Tree-Based Methods
topic Applications
url https://arxiv.org/abs/2409.06046