56 citations · 128 across the 12 of their papers we have counts for
16 papers
Hyperbolic Latent Space Models for Network Embedding: Model Specification and Bayesian Inference
Yiwei Gong, Anna L. Smith, Dena Asta +1
Many real-world networks exhibit hierarchical, tree-like structure and heavy-tailed degree distributions, phenomena not readily captured by standard statistical models for network…
Markov Random Fields: Structural Properties, Phase Transition, and Response Function Analysis
J. Brandon Carter, Catherine A. Calder
This paper presents a focused review of Markov random fields (MRFs)--commonly used probabilistic representations of spatial dependence in discrete spatial domains--for categorical…
Toward a Data Processing Pipeline for Mobile-Phone Tracking Data
Marcin Jurek, Catherine A. Calder, Corwin Zigler +2
As mobile phones become ubiquitous, high-frequency smartphone positioning data are increasingly being used by researchers studying the mobility patterns of individuals as they go a…
Mixture of Directed Graphical Models for Discrete Spatial Random Fields
J. Brandon Carter, Catherine A. Calder
Current approaches for modeling discrete-valued outcomes associated with spatially-dependent areal units incur computational and theoretical challenges, especially in the Bayesian…
Statistical Inference for Complete and Incomplete Mobility Trajectories under the Flight-Pause Model
Marcin Jurek, Catherine A. Calder, Corwin Zigler
We formulate a statistical flight-pause model for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. W…
Land-Use Filtering for Nonstationary Prediction of Collective Efficacy in an Urban Environment
J. Brandon Carter, Christopher R. Browning, Bethany Boettner +2
Collective efficacy -- the capacity of communities to exert social control toward the realization of their shared goals -- is a foundational concept in the urban sociology and neig…
Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods
Moniba Keymanesh, Saket Gurukar, Bethany Boettner +3
Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as soci…
Restricted Spatial Regression Methods: Implications for Inference
Kori Khan, Catherine A. Calder
The issue of spatial confounding between the spatial random effect and the fixed effects in regression analyses has been identified as a concern in the statistical literature. Mult…
Beyond Activity Space: Detecting Communities in Ecological Networks
Wenna Xi, Catherine A. Calder, Christopher R. Browning
Emerging research suggests that the extent to which activity spaces -- the collection of an individual's routine activity locations -- overlap provides important information about…
The Geometry of Continuous Latent Space Models for Network Data
Anna L. Smith, Dena M. Asta, Catherine A. Calder
We review the class of continuous latent space (statistical) models for network data, paying particular attention to the role of the geometry of the latent space. In these models,…
Nonstationary Spatial Prediction of Soil Organic Carbon: Implications for Stock Assessment Decision Making
Mark D. Risser, Catherine A. Calder, Veronica J. Berrocal +1
The Rapid Carbon Assessment (RaCA) project was conducted by the US Department of Agriculture's National Resources Conservation Service between 2010-2012 in order to provide contemp…
Empirical Reference Distributions for Networks of Different Size
Anna Smith, Catherine A. Calder, Christopher R. Browning
Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics…
Local likelihood estimation for covariance functions with spatially-varying parameters: the convoSPAT package for R
Mark D. Risser, Catherine A. Calder
In spite of the interest in and appeal of convolution-based approaches for nonstationary spatial modeling, off-the-shelf software for model fitting does not as of yet exist. Convol…
Regression-based covariance functions for nonstationary spatial modeling
Mark D. Risser, Catherine A. Calder
In many environmental applications involving spatially-referenced data, limitations on the number and locations of observations motivate the need for practical and efficient models…
Bilinear Mixed-Effects Models for Affiliation Networks
Yanan Jia, Catherine A. Calder, Christopher R. Browning
An affiliation network is a particular type of two-mode social network that consists of a set of `actors' and a set of `events' where ties indicate an actor's participation in an e…
Bayesian Spatial Binary Classification
Candace Berrett, Catherine A. Calder
In analyses of spatially-referenced data, researchers often have one of two goals: to quantify relationships between a response variable and covariates while accounting for residua…