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Spatial nonstationarity and autogressive models

Brunsdon, Chris - In: Environment & planning 30 (1998) 6, pp. 957-973

Persistent link: https://www.econbiz.de/10001239603

Some notes on parametric significance tests for geographically weighted regression

Brunsdon, Chris; Fotheringham, Alexander Stewart; … - In: Journal of regional science 39 (1999) 3, pp. 497-524

Persistent link: https://www.econbiz.de/10001397925

Smoothing/filtering LiDAR digital surface models. Experiments with loess regression and discrete wavelets

Tate, Nicholas; Brunsdon, Chris; Charlton, Martin; … - In: Journal of Geographical Systems 7 (2005) 3, pp. 273-290

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The impact of housing consumption value on the spatial distribution of welfare

Kilgarriff, Paul; Charlton, Martin; Foley, Ronan; … - In: Journal of housing economics 43 (2019), pp. 118-130

Persistent link: https://www.econbiz.de/10012268041

The pyrogeography of sub-Saharan Africa: a study of the spatial non-stationarity of fire–environment relationships using GWR

Sá, Ana; Pereira, José; Charlton, Martin; Mota, Bernardo - In: Journal of Geographical Systems 13 (2011) 3, pp. 227-248

Persistent link: https://www.econbiz.de/10009327586

Using circular statistics to analyse spatial flow and temporal data

Corcoran, Jonathan; Brunsdon, Chris - In: Handbook of Research Methods and Applications in …

The chapters in this book provide coverage of the theoretical underpinnings and methodologies that typify research using a Spatially Integrated Social Science (SISS) approach. This insightful Handbook is intended chiefly as a primer for students and budding researchers who wish to investigate...

Persistent link: https://www.econbiz.de/10011171938