5 citations · 11 across the 5 of their papers we have counts for
5 papers
A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation
Jonathan R. Stroud, Matthias Katzfuss, Christopher K. Wikle
This paper proposes new methodology for sequential state and parameter estimation within the ensemble Kalman filter. The method is fully Bayesian and propagates the joint posterior…
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…
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…
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…
Bayesian Spatial Change of Support for Count-Valued Survey Data
Jonathan R. Bradley, Christopher K. Wikle, Scott H. Holan
We introduce Bayesian spatial change of support methodology for count-valued survey data with known survey variances. Our proposed methodology is motivated by the American Communit…