91 citations · 257 across the 49 of their papers we have counts for
5 papers · 2 filters
Bayesian Lattice Filters for Time-Varying Autoregression and Time-Frequency Analysis
Wen-Hsi Yang, Scott H. Holan, Christopher K. Wikle
Modeling nonstationary processes is of paramount importance to many scientific disciplines including environmental science, ecology, and finance, among others. Consequently, flexib…
Bayesian Marked Point Process Modeling for Generating Fully Synthetic Public Use Data with Point-Referenced Geography
Harrison Quick, Scott H. Holan, Christopher K. Wikle +1
Many data stewards collect confidential data that include fine geography. When sharing these data with others, data stewards strive to disseminate data that are informative for a w…
Mixed Effects Modeling for Areal Data that Exhibit Multivariate-Spatio-Temporal Dependencies
Jonathan R. Bradley, Scott H. Holan, Christopher K. Wikle
There are many data sources available that report related variables of interest that are also referenced over geographic regions and time; however, there are relatively few general…
The Cepstral Model for Multivariate Time Series: The Vector Exponential Model
Scott H. Holan, Tucker S. McElroy, Guohui Wu
Vector autoregressive (VAR) models have become a staple in the analysis of multivariate time series and are formulated in the time domain as difference equations, with an implied c…
Bayesian Semiparametric Hierarchical Empirical Likelihood Spatial Models
Aaron T. Porter, Scott H. Holan, Christopher K. Wikle
We introduce a general hierarchical Bayesian framework that incorporates a flexible nonparametric data model specification through the use of empirical likelihood methodology, whic…