Cargando…
Deeper Spatial Statistical Insights into Small Geographic Area Data Uncertainty
Small areas refer to small geographic areas, a more literal meaning of the phrase, as well as small domains (e.g., small sub-populations), a more figurative meaning of the phrase. With post-stratification, even with big data, either case can encounter the problem of small local sample sizes, which t...
Autores principales: | Griffith, Daniel A., Chun, Yongwan, Lee, Monghyeon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795520/ https://www.ncbi.nlm.nih.gov/pubmed/33396823 http://dx.doi.org/10.3390/ijerph18010231 |
Ejemplares similares
-
Space-Time Statistical Insights about Geographic Variation in Lung Cancer Incidence Rates: Florida, USA, 2000–2011
por: Hu, Lan, et al.
Publicado: (2018) -
Soil Sample Assay Uncertainty and the Geographic Distribution of Contaminants: Error Impacts on Syracuse Trace Metal Soil Loading Analysis Results
por: Griffith, Daniel A., et al.
Publicado: (2021) -
Spatial regression analysis using eigenvector spatial filtering
por: Griffith, Daniel, et al.
Publicado: (2019) -
Modeling Community Health with Areal Data: Bayesian Inference with Survey Standard Errors and Spatial Structure
por: Donegan, Connor, et al.
Publicado: (2021) -
Tree species richness predicted using a spatial environmental model including forest area and frost frequency, eastern USA
por: Kwon, Youngsang, et al.
Publicado: (2018)