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Mining boundary effects in areally referenced spatial data using the Bayesian information criterion

Pei Li, Sudipto Banerjee, Alexander M. McBean
2010 Geoinformatica  
We incorporate these edge configurations in spatially autoregressive models and demonstrate how the Bayesian Information Criteria (BIC) can be used to detect difference boundaries in the map.  ...  Statistical models for areal data are primarily used for smoothing maps revealing spatial trends. Subsequent interest often resides in the formal identification of 'boundaries' on the map.  ...  We view our current work as a relatively simple data-mining tool that can suggest influential boundary effects in health maps.  ... 
doi:10.1007/s10707-010-0109-0 pmid:21643463 pmcid:PMC3107044 fatcat:pldestxxqbgx7nxekx23rpfpiy

Bayesian multivariate areal wombling for multiple disease boundary analysis

Haijun Ma, Bradley P. Carlin
2007 Bayesian Analysis  
We identify both composite and cancer-specific boundaries, selecting the best statistical model using the DIC criterion.  ...  Multivariate data summarized over areal units (counties, zip codes, etc.) are common in the field of public health. Estimation or testing of geographic boundaries for such data may have varied goals.  ...  The methods are illustrated using our SEER cancer data in Section 4, where models are compared using the Deviance Information Criterion (DIC; Spiegelhalter et al., 2002) .  ... 
doi:10.1214/07-ba211 fatcat:4xqtpiiapbbmnpw2hajgoglruu

Spatial Modeling of Trends in Crime over Time in Philadelphia [article]

Cecilia Balocchi, Shane T. Jensen
2019 arXiv   pre-print
Bayesian modeling is a promising direction since areal data require principled sharing of information to address spatial autocorrelation between proximal neighborhoods.  ...  We develop several Bayesian approaches to spatial sharing of information between neighborhoods while modeling trends in crime counts over time.  ...  Mining boundary effects in areally referenced spatial data using the Bayesian information criterion. Geoinformatica 15 435–454. Li, G., Haining, R., Richardson, S. and Best, N. (2014).  ... 
arXiv:1901.08117v2 fatcat:45c4sdpsivazflajpzrczwjh5y

Bayesian Wombling for Spatial Point Processes

Shengde Liang, Sudipto Banerjee, Bradley P. Carlin
2009 Biometrics  
In the areal case we can also construct wombled maps showing significant boundaries in the fitted intensity surface, while the point-referenced formulation permits testing the significance of a postulated  ...  In many applications involving geographically indexed data, interest focuses on identifying regions of rapid change in the spatial surface, or the related problem of the construction or testing of boundaries  ...  Minnesota cancer data.  ... 
doi:10.1111/j.1541-0420.2009.01203.x pmid:19302408 pmcid:PMC2795082 fatcat:m72jta55hnd4fnkib3ywyhznki

Spatial and spatio-temporal methods for mapping malaria risk: a systematic review

Julius Nyerere Odhiambo, Chester Kalinda, Peter M Macharia, Robert W Snow, Benn Sartorius
2020 BMJ Global Health  
Findings underscore the need to periodically assess methods and covariates used in malaria risk mapping; to accommodate changes in data availability, data quality and innovation in statistical methodology  ...  BackgroundApproaches in malaria risk mapping continue to advance in scope with the advent of geostatistical techniques spanning both the spatial and temporal domains.  ...  Bayesian hierarchical CAR models are useful for modelling spatially correlated areal data by smoothing noisy estimates and leveraging information from adjacent regions.  ... 
doi:10.1136/bmjgh-2020-002919 pmid:33023880 fatcat:3xe6mn2zp5gw3a55g5ejytdbga

Identifying patterns in spatial information: A survey of methods

Shashi Shekhar, Michael R. Evans, James M. Kang, Pradeep Mohan
2011 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
They are the same as the attributes used in the data inputs of classical data mining.  ...  interpretation: (1) point referenced data, which is modeled as a fixed collection of spatial locations, S, in a two-dimensional framework D (e.g., set of police stations in a metropolitan city); (2) areal  ... 
doi:10.1002/widm.25 fatcat:xqcn7cf5bnbevlm2xlhvpr2gle

Considering spatiotemporal processes in big data analysis: Insights from remote sensing of land cover and land use

Alexis Comber, Michael Wulder
2019 Transactions on GIS  
Using the domain of land cover/land use (LCLU), this article asserts that analyses of big data should be grounded in understandings of underlying process.  ...  The role of proximity in spatial process is well understood, but its value is much more uncertain for many temporal processes.  ...  . 290, emphasis added). and the deviance information criterion (Spiegelhalter, Best, Carlin, & Van Der Linde, 2002), for example, are both suited to Bayesian modeling with posterior model distributions  ... 
doi:10.1111/tgis.12559 fatcat:kcd5cr34evemfoidl6ffpmc2i4

Transductive Learning for Spatial Data Classification [chapter]

Michelangelo Ceci, Annalisa Appice, Donato Malerba
2010 Studies in Computational Intelligence  
the abundance of unlabelled data which potentially convey a large amount of information.  ...  The first three issues are due to the inherent structure of spatial units of analysis, which can be easily accommodated if a (multi-)relational data mining approach is considered.  ...  as well as of the ATENEO-2008 project "Knowledge Discovery in Relational Domains" funded by the University of Bari, Italy.  ... 
doi:10.1007/978-3-642-05177-7_9 fatcat:spbvuwjztbf7zatrug2zyu4oom

Data Semantics [chapter]

2017 Encyclopedia of GIS  
Cross-References Data Infrastructure, Spatial Geography Markup Language (GML) Metadata and Interoperability, Geospatial National Spatial Data Infrastructure (NSDI) OGC's Open Standards for Geospatial Interoperability  ...  Web Mapping and Web Cartography Web Services, Geospatial Cross-References Internet-Based Spatial Information Retrieval Internet GIS  ...  Then, trajectory mining would be used to analyze the movement and change in areal extent of the dynamic regions.  ... 
doi:10.1007/978-3-319-17885-1_100256 fatcat:npcac6ns2zdjfokmwpmzb2s6km

Compositional analysis of topsoil metals and its associations with cancer mortality using spatial misaligned data

Gonzalo López-Abente, Juan Locutura-Rupérez, Pablo Fernández-Navarro, Iván Martín-Méndez, Alejandro Bel-Lan, Olivier Núñez
2017 Environmental Geochemistry and Health  
This model included soil sample locations and town centroids (non-aligned data), fitted using the integrated nested Laplace approximation (INLA) as a tool for Bayesian inference and stochastic partial  ...  The presence of toxic metals in soil per se, and in soil impacted by mining, industry, agriculture and urbanisation in particular, is a major concern for both human health and ecotoxicology.  ...  Mortality data were supplied by the Spanish National Statistics Institute in accordance with a specific confidentiality protocol. Environ Geochem Health  ... 
doi:10.1007/s10653-016-9904-3 pmid:28155030 pmcid:PMC5797570 fatcat:j5p7auii3fci5hjc3c6whdm5t4

An Integrated Framework of Population Change: Influential Factors, Spatial Dynamics, and Temporal Variation

2011 Growth and Change  
Population geographers are interested in spatial variations of population distribution, density, composition, and growth (Bailey 2005).  ...  Population change has been studied in the fields of human ecology, population geography, environmental sociology, transportation planning, and regional economics, which make unique contributions to theorizing  ...  Finally, the OLS models as well as the spatial regression models should be evaluated on the basis of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to provide estimates of  ... 
doi:10.1111/j.1468-2257.2011.00567.x fatcat:r2xq7izf5vajtbyxgveacc7p3q

Access Method [chapter]

2017 Encyclopedia of GIS  
of databases; Geographic data reduction; Model generalization; Multiple resolution database Definition Model generalization is used to derive a more simple and more easy to handle digital representation  ...  Model generalization is also called geodatabase abstraction, as it relates to generating a more simple digital representation of geometric objects in a database, leading to a considerable data reduction  ...  Cross-References Accuracy, Map Imprecision and Spatial Uncertainty Accuracy, Spatial Imprecision and Spatial Uncertainty Active Data Mining Gaussian Process Models in Spatial Data Mining ActiveX  ... 
doi:10.1007/978-3-319-17885-1_100021 fatcat:ruj53dunmjhihjmn2svftoof2a

Analysing surnames as geographic data

James Cheshire
2014 Journal of Anthropological Sciences  
The review discusses the emerging applications for surname research, not least in the mining of online data, and ends by suggesting three future research themes to ensure the building momentum of surname  ...  With most surname research undertaken within the fields of anthropology and population genetics, geographers have overlooked surnames as a credible data source.  ...  data -the Modifiable Areal Unit Problem (MAUP) (see Openshaw, 1984) .  ... 
doi:10.4436/jass.92004 pmid:25020015 fatcat:vn3o3qagxjai7hzpaegnfv6g6i

Spatial and Spatio-Temporal Log-Gaussian Cox Processes: Extending the Geostatistical Paradigm

Peter J. Diggle, Paula Moraga, Barry Rowlingson, Benjamin M. Taylor
2013 Statistical Science  
In this paper we first describe the class of log-Gaussian Cox processes (LGCPs) as models for spatial and spatio-temporal point process data.  ...  We then demonstrate the usefulness of the LGCP by describing four applications: estimating the intensity surface of a spatial point process; investigating spatial segregation in a multi-type process; constructing  ...  to use the Spanish lung cancer data.  ... 
doi:10.1214/13-sts441 fatcat:emi3b3konvaojcvnkcw73td4ym

Modelling the dynamic pattern of surface area in basketball and its effects on team performance

Rodolfo Metulini, Marica Manisera, Paola Zuccolotto
2018 Journal of Quantitative Analysis in Sports (JQAS)  
We carry out the proposed procedure using real data and, in the analyzed case studies, we find that structural changes are strongly associated to offensive and defensive game phases and that there is some  ...  big data analytics.  ...  We use a modified Bayesian information criterion to estimate the number of sequence variants, and obtain maximum likelihood estimates of the abundance and identity of variants.  ... 
doi:10.1515/jqas-2018-0041 fatcat:b3qwsi7tqjg2vdo7gbjtiorv6m
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