The DOI matches its Crossref record.
Methods and Techniques in Human Geography
Abstract
Exploring geographical data testing hypotheses measuring associations multivariate analysis generalized linear models and categorical data analysis spatial allocation spatial interaction spatial datatistics, spatial models and spatial structure space and time systems and geographical information systems investigating behaviour and perception qualitative methods Marxist analysis in human geography feminist geographies postmodern geographies.
Overview
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Citations
Cited by
Hybrids of gibbs point process models and their implementation
Baddeley, A., Turner, R., Mateu, J., & Bevan, A. (2013) · Journal of Statistical Software · doi:10.18637/jss.v055.i11 · Cited by 52
Exploratory network reconstruction with sparse archaeological data and XTENT
Ducke, B., & Suchowska, P. (2022) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-021-09529-3 · Cited by 12
Metadata
- Authors
- Rogerson, P., & Robinson, G. M.
- Venue
- Economic Geography
- Publisher
- JSTOR
- Published
- 2000-01
- Volume
- 76
- Issue
- 1
- Pages
- 105
- ISSN
- 0013-0095 (ISSN-L)
- OpenAlex
- W2028031877
- Cited by
- 288
- References
- 0
- FWCI
- 26.31
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
