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Full-Text Articles in Physical Sciences and Mathematics
Texture Analysis Using Partially Ordered Markov Models, Jennifer Davidson, Ashit Talukder, Noel A. Cressie
Texture Analysis Using Partially Ordered Markov Models, Jennifer Davidson, Ashit Talukder, Noel A. Cressie
Professor Noel Cressie
Texture is a phenomenon in image data that continues to receive wide-spread interest due to its broad range of applications. The paper focuses on but one of several ways to model textures, namely, the class of stochastic texture models. the authors introduce a new spatial stochastic model called partially ordered Markov models, or POMMs. They show how POMMs are a generalization of a class of models called Markov mesh models, or MMMs, that allow an explicit closed form of the joint probability, just as do MMMs. While POMMs are a type of Markov random field model (MRF), the general MRFs …
A Spatial Analysis Of Multivariate Output From Regional Climate Models, Stephan Sain, Reinhard Furrer, Noel A. Cressie
A Spatial Analysis Of Multivariate Output From Regional Climate Models, Stephan Sain, Reinhard Furrer, Noel A. Cressie
Professor Noel Cressie
Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output. However, there are often only a limited number of model runs available for a particular experiment, and one of the statistical challenges is to characterize the distribution of the model output. To that end, we have developed a multivariate hierarchical approach, at the heart of which is a new representation of a multivariate Markov random field. This approach allows for flexible modeling of the multivariate spatial …
A Spatial Analysis Of Variance Applied To Soil-Water Infiltration, C Gotway, Noel A. Cressie
A Spatial Analysis Of Variance Applied To Soil-Water Infiltration, C Gotway, Noel A. Cressie
Professor Noel Cressie
A spatial analysis of variance uses the spatial dependence among the observations to modify the usual interference procedures associated with a statistical linear model. When spatial correlation is present, the usual tests for presence of treatment effects may no longer be valid, and erroneous conclusions may result from assuming that the usual F ratios are F distributed. This is demonstrated using a spatial analysis of soil-water infiltration data. Emphasis is placed on modeling the spatial dependence structure with geostatistical techniques, and this spatial dependence structure is then used to test hypotheses about fixed effects using a nested linear model. -Authors
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Bayesian Hierarchical Analysis Of Minefield Data, Noel A. Cressie, Andrew B. Lawson
Professor Noel Cressie
Based on remote sensing of a potential minefield, point locations are identified, some of which may not be mines. The mines and mine-like objects are to be distinguished based on their point patterns, although it must be emphasized that all we see is the superposition of their locations. In this paper, we construct a hierarchical spatial point-process model that accounts for the different patterns of mines and mine-like objects and uses posterior analysis to distinguish between them. Our Bayesian approach is applied to COBRA image data obtained from the NSWC Coastal Systems Station, Dahlgren Division, Panama City, Florida. 2003 Copyright …
A Robust-Resistant Spatial Analysis Of Soil Water Infiltration., Noel A. Cressie, R Horton
A Robust-Resistant Spatial Analysis Of Soil Water Infiltration., Noel A. Cressie, R Horton
Professor Noel Cressie
Concentrates on estimating the spatial correlations between soil water infiltration observations, with special emphasis on resistant methods to remove nonstationarity. After this removal, robust semivariogram estimators are used to examine the spatial dependencies for various tillage treatments. There is some indication that infiltration characteristics inherit different types of spatial dependency, depending on the tillage treatment applied.-from Authors