Pages that link to "Item:Q2903317"
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The following pages link to Boundary detection in disease mapping studies (Q2903317):
Displaying 14 items.
- Clustering the prevalence of pediatric chronic conditions in the United States using distributed computing (Q1624814) (← links)
- Improved inference for areal unit count data using graph-based optimisation (Q2058788) (← links)
- Spatial modeling of trends in crime over time in Philadelphia (Q2291513) (← links)
- Spatial Boundary Detection for Areal Counts (Q2800207) (← links)
- Estimation of risk surfaces and identification of district boundaries for tuberculosis in North-Eastern Indian states (Q2820239) (← links)
- Spatial clustering of average risks and risk trends in Bayesian disease mapping (Q2956822) (← links)
- Areal prediction of survey data using Bayesian spatial generalised linear models (Q5083913) (← links)
- Spatio-temporal model for crop yield forecasting (Q5138547) (← links)
- A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution (Q5170213) (← links)
- Computational Science – ICCS 2005 (Q5709709) (← links)
- Discussion of “Statistical disease mapping for heterogeneous neuroimaging studies” (Q6059485) (← links)
- Identifying boundaries in spatially continuous risk surfaces from spatially aggregated disease count data (Q6138628) (← links)
- Inducing high spatial correlation with randomly edge-weighted neighborhood graphs (Q6203350) (← links)
- Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration (Q6627539) (← links)
