Browsing by Subject "spatial statistics"
Now showing items 1-9 of 9
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(2021-06-02)Gaussian processes are a powerful and flexible class of nonparametric models that use covariance functions, or kernels, to describe correlations across data. In addition to expressing realistic assumptions, correlation ...
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(2021-04-12)This dissertation explores various applications of Bayesian hierarchical modeling to accommodate general characteristics of the modern data: complex data structure, high-dimensionality, and huge data size. The focus of the ...
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(2018-11-26)Plant breeders must improve the efficiency of their programs to meet the needs of a rising world population and a rapidly changing climate. Proximal and remote sensing technologies stand as an attractive option for breeders, ...
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(2020-11-18)Gaussian processes (GPs) are widely used in geospatial analysis, machine learning and many application areas. We propose novel scalable methods to tackle two problems in Gaussian process modeling for large spatial datasets. In ...
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Geographies of identity theft in the u.s.: understanding spatial and demographic patterns, 2002-2006 (2009-05-15)Criminal justice researchers and crime geographers have long recognized the importance of understanding where crimes happen as well as to whom and by whom. Although past research often focused on violent crimes, calls for ...
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(2011-10-21)In this dissertation, we explore the properties of correlation structure for spatio-temporal point processes and a quantitative spatial process. Spatio-temporal point processes are often assumed to be separable; we propose ...
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(2012-02-14)In recent years, the application of resampling methods to dependent data, such as time series or spatial data, has been a growing field in the study of statistics. In this dissertation, we discuss two such applications. In ...
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(2022-08-17)Background: Two cancer clusters near potential contaminate sites have recently been identified in Northeast Houston, Texas. A Creosote plume from the Englewood Rail Yards wood treatment processes during the early 1900s to ...
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(2020-06-09)Spatial random fields are widely used to model the space-time correlation structure of different objects in various fields, such as the soil moisture field in hydrological, agricultural and climatological studies. Since ...