Thèses sur le sujet « Hierarchical spatial modeling »
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Ma, Pulong. « Hierarchical Additive Spatial and Spatio-Temporal Process Models for Massive Datasets ». University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535635193581096.
Texte intégralThomas, Zachary Micah. « Bayesian Hierarchical Space-Time Clustering Methods ». The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1435324379.
Texte intégralSengupta, Aritra. « Empirical Hierarchical Modeling and Predictive Inference for Big, Spatial, Discrete, and Continuous Data ». The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1350660056.
Texte intégralKatzfuss, Matthias. « Hierarchical Spatial and Spatio-Temporal Modeling of Massive Datasets, with Application to Global Mapping of CO2 ». The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1308316063.
Texte intégralShi, Hongxiang. « Hierarchical Statistical Models for Large Spatial Data in Uncertainty Quantification and Data Fusion ». University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504802515691938.
Texte intégralLi, Linhua. « A GIS-based Bayesian approach for analyzing spatial-temporal patterns of traffic crashes ». [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1766.
Texte intégralPfarrhofer, Michael, et Philipp Piribauer. « Flexible shrinkage in high-dimensional Bayesian spatial autoregressive models ». Elsevier, 2019. http://epub.wu.ac.at/6839/1/1805.10822.pdf.
Texte intégralRoss, Beth E. « Assessing Changes in the Abundance of the Continental Population of Scaup Using a Hierarchical Spatio-Temporal Model ». DigitalCommons@USU, 2012. http://digitalcommons.usu.edu/etd/1147.
Texte intégralRice, Ketra Lachell. « A Multi-Method Analysis of the Role of Spatial Factors in Policy Analysis and Health Disparities Research ». The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365613669.
Texte intégralAcar, Alper. « Optimal Urban Planning and Housing Prices : a Spatial Analysis ». Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCG008.
Texte intégralThis dissertation studies the effect of optimal urban planning on housing prices diffusion in local real-estate markets. The study uses facility location theory and spatial econometrics to investigate how graph properties and optimal location models can contribute to a better understanding and evaluation of the impact of spatial multiplier effects in the economy. To this end, the research is based on a methodology that combines the creation of decision-support tools and the study of real estate prices using hierarchical spatial econometric models. The results states that using optimal spatial relationships enables a more precise analysis of the impacts of urban planning on the diffusion of prices. Conversely, the consideration of “classical” spatial relationships either underestimates or overestimates the spatial impacts
Liu, Jia. « Heterogeneous Sensor Data based Online Quality Assurance for Advanced Manufacturing using Spatiotemporal Modeling ». Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78722.
Texte intégralPh. D.
Alglave, Baptiste. « Inférer la distribution spatio-temporelle des espèces d’intérêt halieutique et identifier leurs habitats essentiels : modéliser l’échantillonnage préférentiel et le changement de support pour intégrer des sources de données hétérogènes ». Electronic Thesis or Diss., Rennes, Agrocampus Ouest, 2022. http://www.theses.fr/2022NSARH117.
Texte intégralMapping fish distribution and identifying fish essential habitats grounds is key to ensure species renewal and manage the marine space. Information on the location of fish essential habitats and specifically of fish spawning grounds is still lacking for many harvested species.The reference data to map fish distribution and identify spawning grounds are scientific survey data. These data benefit from a standardized sampling protocol. However, due to their costs, they also generally suffer from a low sampling density in space and time. In particular, they generally occur once or twice a year and they may mismatch fish reproduction.Commercial declarations combined with Vessel Monitoring System data could prove highly valuable to complement the information brought by scientific survey data as fishermen landings provide information on the full year with a much denser sampling density. In this PhD, we developed an integrated statistical framework that allows to combine commercial and scientific data sources to infer fish distribution in space and time. Our approach accounts for fishermen targeting behavior towards areas of higher biomass (preferential sampling) and allows to infer fine scale species distribution based on spatially aggregated declarations data (change of support). We demonstrate the ability of the framework to produce monthly maps of fish distribution and to identify aggregation areas during reproduction season. We also outline the potential applications of the framework for Marine Spatial Planning and discuss several extensions that could be added to the actual model
Southey, Richard. « Bayesian hierarchical modelling with application in spatial epidemiology ». Thesis, Rhodes University, 2018. http://hdl.handle.net/10962/59489.
Texte intégralFlask, Thomas V. « An Application of Multi-Level Bayesian Negative Binomial Models with Mixed Effects on Motorcycle Crashes in Ohio ». University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1333046055.
Texte intégralWang, Shuang. « Novel approaches for patterning hierarchical hydrogels ». Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/121231/1/Shuang_Wang_Thesis.pdf.
Texte intégralZhuang, Lili. « Bayesian Dynamical Modeling of Count Data ». The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1315949027.
Texte intégralBrynjarsdóttir, Jenný. « Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling ». The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1312935520.
Texte intégralBaker, Jannah F. « Bayesian spatiotemporal modelling of chronic disease outcomes ». Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/104455/1/Jannah_Baker_Thesis.pdf.
Texte intégralDou, Yiping. « Dynamic Bayesian models for modelling environmental space-time fields ». Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/634.
Texte intégralLow, Choy Samantha Jane. « Hierarchical models for 2D presence/absence data having ambiguous zeroes : With a biogeographical case study on dingo behaviour ». Thesis, Queensland University of Technology, 2001. https://eprints.qut.edu.au/37098/12/Samantha%20Low%20Choy%20Thesis.pdf.
Texte intégralIddrisu, Abdul-Karim. « Bayesian hierarchical spatial and spatio-temporal modeling and mapping of tuberculosis in Kenya ». Thesis, 2013. http://hdl.handle.net/10413/10279.
Texte intégralThesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.
Pittman, Tyler. « The Association Between Neighbourhood Stressors and Asthma Prevalence of School Children in Winnipeg ». Master's thesis, 2011. http://hdl.handle.net/10048/1917.
Texte intégralLee, JaeYoung. « Development of Traffic Safety Zones and Integrating Macroscopic and Microscopic Safety Data Analytics for Novel Hot Zone Identification ». Doctoral diss., 2014. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6127.
Texte intégralPh.D.
Doctorate
Civil, Environmental and Construction Engineering
Engineering and Computer Science
Civil Engineering
MINGIONE, MARCO. « On the wide applicability of Bayesian hierarchical models ». Doctoral thesis, 2022. http://hdl.handle.net/11573/1613592.
Texte intégral