The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Comparing Implementations of Estimation Methods for Spatial Econometrics
Open accessAbstract
Recent advances in the implementation of spatial econometrics model estimation techniques have made it desirable to compare results, which should correspond between implementations across software applications for the same data. These model estimation techniques are associated with methods for estimating impacts (emanating effects), which are also presented and compared. This review constitutes an up-to-date comparison of generalized method of moments and maximum likelihood implementations now available. The comparison uses the cross-sectional US county data set provided by Drukker, Prucha, and Raciborski (2013d). The comparisons will be cast in the context of alternatives using the MATLAB Spatial Econometrics toolbox, Stata's user-written sppack commands, Python with PySAL and R packages including spdep, sphet and McSpatial.
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R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
nlme : Linear and nonlinear mixed effects models
DebRoy, S. (2006) · Medical Entomology and Zoology · Cited by 10,009
Spatial Econometrics: Methods and Models
Anselin, L. (1988) · Studies in Operational Regional Science · doi:10.1007/978-94-015-7799-1 · Cited by 9,274
Applied Spatial Data Analysis with R
Bivand, R. S., Pebesma, E., & Gómez-Rubio, V. (2013) · Springer eBooks · doi:10.1007/978-1-4614-7618-4 · Cited by 3,206
Self-citationAn Introduction to Spatial Econometrics
LeSage, J. P. (2008) · Revue d'économie industrielle · doi:10.4000/rei.3887 · Cited by 2,998
Algorithms for Minimization Without Derivatives
G., D., & Brent, R. P. (1974) · Mathematics of Computation · doi:10.2307/2005713 · Cited by 2,847
Ripley, B. D. (1981) · Cited by 2,819
GeoDa: An Introduction to Spatial Data Analysis
Anselin, L., Syabri, I., & Kho, Y. (2006) · Geographical Analysis · doi:10.1111/j.0016-7363.2005.00671.x · Cited by 2,555
Kelejian, H. H., & Prucha, I. R. (1998) · The Journal of Real Estate Finance and Economics · doi:10.1023/a:1007707430416 · Cited by 1,976
Simple diagnostic tests for spatial dependence
Anselin, L., Bera, A. K., Florax, R., & Yoon, M. J. (1996) · Regional Science and Urban Economics · doi:10.1016/0166-0462(95)02111-6 · Cited by 1,850
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Hou, E., Luo, Y., Kuang, Y., Chen, C., Lu, X., Jiang, L., Luo, X., & Wen, D. (2020) · Nature Communications · doi:10.1038/s41467-020-14492-w · Cited by 760
Exploring the reservoir of potential fungal plant pathogens in agricultural soil
Agtmaal, M. V., Straathof, A., Termorshuizen, A., Teurlincx, S., Hundscheid, M., Ruyters, S., Busschaert, P., Lievens, B., & Boer, W. D. (2017) · Applied Soil Ecology · doi:10.1016/j.apsoil.2017.09.032 · Cited by 62
Metadata
- Authors
- Bivand, R., & Piras, G.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2015
- Volume
- 63
- Issue
- 18
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W2156127902
- Cited by
- 939
- References
- 43
- FWCI
- 292.31
- Type
- journal article
- Language
- en
- Open access
- diamond
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