Browsing Department of Statistics (MU) by Author "Wikle, Christopher K., 1963"
Now showing items 110 of 10

Accounting for Uncertainty in Ecological Analysis: The Strengths and Limitations of Hierarchical Statistical Modeling
Cressie, Noel A. C.; Calder, Catherine A., 1976; Clark, James Samuel, 1957; Ver Hoef, Jay M.; Wikle, Christopher K., 1963 (Ecological Society of America, 200904)Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. ... 
Efficient Statistical Mapping of Avian Count Data
Royle, J. Andrew; Wikle, Christopher K., 1963 (Environmental and Ecological Statistics, 2005)We develop a spatial modeling framework for count data that is efficient to implement in highdimensional prediction problems. We consider spectral parameterizations for the spatially varying mean of the Poisson model. The ... 
Hierarchical Bayesian Approach to Boundary Value Problems with Stochastic Boundary Conditions
Wikle, Christopher K., 1963; Berliner, L. Mark; Milliff, Ralph F. (American Meteorological Society, 2003)Boundary value problems are ubiquitous in the atmospheric and ocean sciences. Typical settings include bounded, partially bounded, global and limited area domains, discretized for applications of numerical models of the ... 
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes
Wikle, Christopher K., 1963 (Ecological Society of America, 2003)There is increasing interest in predicting ecological processes. Methods to accomplish such predictions must account for uncertainties in observation, sampling, models, and parameters. Statistical methods for spatiotemporal ... 
A Hierarchical Bayesian Nonlinear Spatiotemporal Model for the Spread of Invasive Species with Application to the Eurasian CollaredDove
Hooten, Mevin B., 1976; Wikle, Christopher K., 1963 (Environmental and Ecological Statistics, 2007)Differential equation based advectiondiffusion models have been used in atmospheric science to mimic complex processes such as weather and climate. Differential and partialdifferential equations (PDE's) have become popular ... 
A KernelBased Spectral Model for NonGaussian SpatioTemporal Processes
Wikle, Christopher K., 1963 (Statistical Modelling, 2002)Spatiotemporal processes can often be written as hierarchical statespace processes. In situations with complicated dynamics such as wave propagation, it is difficult to parameterize state transition functions for ... 
Multiresolution Models for Nonstationary Spatial Covariance Functions
Nychka, Douglas; Wikle, Christopher K., 1963; Royle, J. Andrew (Statistical Modelling, 2002)Many geophysical and environmental problems depend on estimating a spatial process that has nonstationary structure. A nonstationary model is proposed based on the spatial field being a linear combination of a multiresolution ... 
Predicting the Spatial Distribution of Ground Flora on Large Domains Using a Hierarchical Bayesian Model
Hooten, Mevin B., 1976; Larsen, David R. (David Rolf); Wikle, Christopher K., 1963 (Landscape Ecology, 2003)Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural ... 
Shifts in the SpatioTemporal Growth Dynamics of Shortleaf Pine
Hooten, Mevin B., 1976; Wikle, Christopher K., 1963 (Environmental and Ecological Statistics, 2007)Previous studies focusing on the growth history of pinus echinata at the edge of its geographical range have suggested that changes in growth correspond to climatic and nonclimatic (e.g., anthropogenic) factors. We employ ... 
SpatioTemporal Hierarchical Bayesian Modeling: Tropical Ocean Surface Winds
Wikle, Christopher K., 1963; Milliff, Ralph F.; Nychka, Douglas; Berliner, L. Mark (American Statistical Association, 2001)Spatiotemporal processes are ubiquitous in the environmental and physical sciences. This is certainly true of atmospheric and oceanic processes, which typically exhibit many different scales of spatial and temporal ...