Chris Brunsdon
Economics and Econometrics · 2001–2013
A researcher in the Science corpus: 10 papers; trusts 19 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Economics and Econometrics — 33 citations into it; #3,880 of 23,481 by trust here, #3,986 by citations
- Statistics and Probability — 28 citations into it
- Environmental Engineering — 16 citations into it
- Global and Planetary Change — 14 citations into it; #6,868 of 10,225 by trust here, #7,962 by citations
- Artificial Intelligence — 12 citations into it
- Applied Mathematics — 6 citations into it
- Optimization & Training — 5 citations into it
Whom Chris Brunsdon trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David C. Wheeler
- Bernard Walter Silverman
- Edzer J. Pebesma
- William S. Cleveland
- Robert M. O’Brien
- Jerome H. Friedman
- Martin Charlton
- Tomoki Nakaya
- S. Fotheringham
- David Wheeler
Who trusts Chris Brunsdon overall
- Binbin Lu
- Isabella Gollini
- Martin Charlton
- Philip Kostov
- Maryam Kordi
- Paul Harris
- A. Stewart Fotheringham
- Jingru Mu
- Seong‐Hoon Cho
- Dayton M. Lambert
Papers from Chris Brunsdon's perspective
Ordered by how strongly the researchers Chris Brunsdon trusts endorse each paper. Same corpus, a different order for every researcher.
- Geostatistics for Natural Resources Evaluation
- Simultaneous Coefficient Penalization and Model Selection in Geographically Weighted Regression: The Geographically Weighted Lasso
- Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model
- Diagnostic Tools and a Remedial Method for Collinearity in Geographically Weighted Regression
- Generalized Linear Models
- Links, comparisons and extensions of the geographically weighted regression model when used as a spatial predictor
- Nonparametric Regression and Generalized Linear Models: A roughness penalty approach
- Local Regression and Likelihood
- Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity
- Geographically weighted Poisson regression for disease association mapping (Statistics in Medicine)
Their papers
- Geographically weighted Poisson regression for disease association mapping (2005) — 545 citations
- GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models (2013) — 582 citations
- Links, comparisons and extensions of the geographically weighted regression model when used as a spatial predictor (2011) — 60 citations
- Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (2010) — 3,163 citations
- Spatial Variations in School Performance: A Local Analysis Using Geographically Weighted Regression (2001) — 248 citations
- Principal Component Analysis on Spatial Data: An Overview (2013) — 453 citations
- Living with Collinearity in Local Regression Models (2012) — 47 citations
- Semiparametric geographically weighted generalisedlinear modelling in GWR 4.0 (2009) — 123 citations
- Geographically weighted summary statistics — aframework for localised exploratory data analysis (2002) — 263 citations
- Linking serious sexual assaults through behaviour (2001) — 109 citations