10 citations · 35 across the 13 of their papers we have counts for
13 papers
Pointwise density estimation on metric spaces and applications in seismology
Galatia Cleanthous, Athanasios G. Georgiadis, Philip A. White
We are studying the problem of estimating density in a wide range of metric spaces, including the Euclidean space, the sphere, the ball, and various Riemannian manifolds. Our frame…
Joint Multivariate and Functional Modeling for Plant Traits and Reflectances
Philip A. White, Michael F. Christensen, Henry Frye +2
The investigation of leaf-level traits in response to varying environmental conditions has immense importance for understanding plant ecology. Remote sensing technology enables mea…
Nonseparable Space-Time Stationary Covariance Functions on Networks cross Time
Emilio Porcu, Philip A. White, Marc G. Genton
The advent of data science has provided an increasing number of challenges with high data complexity. This paper addresses the challenge of space-time data where the spatial domain…
Spatial Functional Data Modeling of Plant Reflectances
Philip A. White, Henry Frye, Michael F. Christensen +2
Plant reflectance spectra - the profile of light reflected by leaves across different wavelengths - supply the spectral signature for a species at a spatial location to enable esti…
Flexible Validity Conditions for the Multivariate Matérn Covariance in any Spatial Dimension and for any Number of Components
Xavier Emery, Emilio Porcu, Philip White
This paper addresses the problem of finding parametric constraints that ensure the validity of the multivariate Mat{é}rn covariance for modeling the spatial correlation structure o…
Improving Piecewise Linear Snow Density Models through Hierarchical Spatial and Orthogonal Functional Smoothing
Philip White, Durban Keeler, Daniel Sheanshang +1
Snow density estimates as a function of depth are used for understanding climate processes, evaluating water accumulation trends in polar regions, and estimating glacier mass balan…
Hierarchical Integrated Spatial Process Modeling of Monotone West Antarctic Snow Density Curves
Philip A. White, Durban G. Keeler, Summer Rupper
Snow density estimates below the surface, used with airplane-acquired ice-penetrating radar measurements, give a site-specific history of snow water accumulation. Because it is inf…
Generalized Evolutionary Point Processes: Model Specifications and Model Comparison
Philip A. White, Alan E. Gelfand
Generalized evolutionary point processes offer a class of point process models that allows for either excitation or inhibition based upon the history of the process. In this regard…
Multivariate Functional Data Modeling with Time-varying Clustering
Philip A. White, Alan E. Gelfand
We consider the situation where multivariate functional data has been collected over time at each of a set of sites. Our illustrative setting is bivariate, monitoring ozone and PM$…
Modeling Daily Seasonality of Mexico City Ozone using Nonseparable Covariance Models on Circles Cross Time
Philip A. White, Emilio Porcu
Mexico City tracks ground-level ozone levels to assess compliance with national ambient air quality standards and to prevent environmental health emergencies. Ozone levels show dis…
Pollution State Modeling for Mexico City
Philip A. White, Alan E. Gelfand, Eliane R. Rodrigues +1
Ground-level ozone and particulate matter pollutants are associated with a variety of health issues and increased mortality. For this reason, Mexican environmental agencies regulat…
Towards a Complete Picture of Stationary Covariance Functions on Spheres Cross Time
Philip White, Emilio Porcu
With the advent of wide-spread global and continental-scale spatiotemporal datasets, increased attention has been given to covariance functions on spheres over time. This paper pro…
Modeling Efficiency of Foreign Aid Allocation in Malawi
Philip A. White, Candace Berrett, E. Shannon Neeley-Tass +1
The Open Aid Malawi initiative has collected an unprecedented database that identifies as much location-specific information as possible for each of over 2500 individual foreign ai…