38 results on '"Oshan, Taylor M."'
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2. Are we breaking bubbles as we move? Using a large sample to explore the relationship between urban mobility and segregation
3. Navigating the Methodological Landscape in Spatial Analysis: A Comment on “A Route Map for Successful Applications of Geographically-Weighted Regression”
4. Targeting the spatial context of obesity determinants via multiscale geographically weighted regression
5. Geographically weighted regression and multicollinearity: dispelling the myth
6. Navigating the Methodological Landscape in Spatial Analysis: A Comment on “A Route Map for Successful Applications of Geographically‐Weighted Regression”
7. Local Modeling in a Regression Framework
8. Spatial Interaction Modeling
9. Navigating the Methodological Landscape in Spatial Analysis: A Comment on "A Route Map for Successful Applications of Geographically‐Weighted Regression".
10. Comparing spatial interaction models and flow interpolation techniques for predicting 'cold start' bike-share trip demand
11. On the notion of ‘bandwidth’ in geographically weighted regression models of spatially varying processes
12. A Scoping Review on the Multiplicity of Scale in Spatial Analysis
13. mgwr: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale
14. The PySAL Ecosystem: Philosophy and Implementation.
15. arcos (R) and arcospy (Python): twin software packages to access the DEA ARCOS database from 2006 to 2014
16. The PySAL Ecosystem: Philosophy and Implementation
17. On Null Hypotheses and Heteroskedasticity
18. The spatial structure debate in spatial interaction modeling: 50 years on
19. The spatial structure debate in spatial interaction modeling: 50 years on
20. Potential and Pitfalls of Big Transport Data for Spatial Interaction Models of Urban Mobility
21. Are we breaking bubbles as we move? Exploring the relationship between urban mobility and segregation
22. Process indicator-of-scale metrics – PRISMs
23. Targeting the spatial context of obesity determinants via multiscale geographically weighted regression
24. Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
25. Open Code is not enough: Towards a replicable future for geographic data science
26. The spatial structure debate in spatial interaction modeling: 50 years on.
27. A primer for working with the Spatial Interaction modeling (SpInt) module in the python spatial analysis library (PySAL)
28. Single and Multiscale Models of Process Spatial Heterogeneity
29. Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
30. Replicability and reproducibility through the lens of local statistical modeling
31. A multiscale spatial analysis of obesity determinants in Phoenix, Arizona
32. On the Measurement of Bias in Geographically Weighted Regression Models
33. mgwr: A Python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale
34. Inference in multiscale geographically weighted regression
35. Single and Multiscale Models of Process Spatial Heterogeneity
36. A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial-Filter-Based Techniques
37. A primer for working with the Spatial Interaction modeling (SpInt) module in the python spatial analysis library (PySAL)
38. A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial‐Filter‐Based Techniques.
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