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References
Anselin, L. 1988. Model validation in spatial econometrics: a review and evaluation of alternative approaches. International Regional Science Review 11:279-316.
Anselin, L. 2001. Spatial Regression. http://geog55.gis.uiuc.edu/Ëœluc/talks/spreg.pdf.
Bavaud, F. 1998. Models for spatial weights: a systematic look. Geographical Analysis 30:153-171.
Berk, R. 2003. Regression Analysis A Constructive Critique. Sage Publications, Newbury Park CA.
Cook, R. D., and S. Weisberg. 1999. Applied Regression Including Computing and Graphics. Wiley.
Cressie, N. 1991. Statistics for Spatial Data. Wiley.
de Leeuw, J. 1994. Block relaxation methods in statistics. Pages 275-289 in H. H. Bock, W. Lenski, and M. M. Richter, editors. Information Systems and Data Analysis. Springer, New York.
de Leeuw, J., and I. G. G. Kreft. 2001. Software for multilevel analysis. Pages 187-204 in A. H. Leyland and H. Goldstein, editors. Multilevel Modelling of Health Statistics. Wiley, New York.
Goldstein, H. 1995. Multilevel Statistical Medels. Arnold.
Griffith, D. A. 2002a. Quick but not so Dirty. ML Estimation of Spatial Autoregressive Models. Technical Report. Department of Geography, Syracuse University, Syracuse, NY.
Griffith, D. A. 2002b. Spatial Autoregression. Syracuse University, Syracuse, NY. Hedeker, D. R. 1989. Random Regression Models with Autocorrelated Errors: Investigating Drug Plasma Levels and Clinical Response. Ph.D. Thesis. University of Chicago at Illinois, Chicago, IL.
Hedeker, D. R., and R. D. Gibbons. 1996. MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors. Computer Methods and Programs in Biomedicine 49:229-252.
Kreft, I., and J. de Leeuw. 1998. Introducing Multilevel Modeling. Sage Publications, Newbury Park CA.
Littell, R. C., G. A. Milliken, W. W. Stroup, and R. D. Wolfinger. 1996. SAS System for Mixed Models. SAS Institute, Cary NC.
Longford, N. 1993. Random Coefficient Models. Oxford University Press, Oxford.
Ord, J. K. 1975. Estimation methods for models of spatial interactions. Journal of the American Statistical Association 70:120-127.
Pace, R. K., and R. Barry. 1997a. Fast CARs. Journal of Statistical Compution and Simulation 59:123-147.
Pace, R. K., and R. Barry. 1997b. Quick computation of spatial autoregressive estimators. Geographical Analysis 29:232-246.
Pace, R. K., and R. Barry. 1997c. Sparse spatial autoregressions. Statistics and Probability Letters 33:191-197.
Pace, R. K., and D. Zou. 2000. Closed-form maximum likelihood estimates of nearest neighbor spatial dependence. Geographic Analysis 32:154-172.
Page, R. K., and J. P. LeSage. 2002. Conditional Autoregressions with Doubly Stochastic Weight Matrices (manuscript).
Rabe-Hesketh, S., A. Skrondal, and A. Pickles. 2002. Reliable estimation of generalized linear mixed models using adaptive quadrature. The Stata Journal 2:1-21.
Raudenbush, S. W., and A. S. Bryk. 2002. Hierarchical Linear Models, second edition, second edition. Sage Publications, Newbury Park, CA.
Smirnov, O., and A. Anselin. 2001. Fast maximum likelihood estimation of very large spatial auto-regressive models. Computational Statistics and Data Analysis 35:301-319.
Wu, J. 1999. Hierarchy and scaling: extrapolating information along a scaling ladder. Canadian Journal of Remote Sensing 25:367-380.
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Berk, R.A., de Leeuw, J. (2006). MULTILEVEL STATISTICAL MODELS AND ECOLOGICAL SCALING. In: WU, J., JONES, K.B., LI, H., LOUCKS, O.L. (eds) SCALING AND UNCERTAINTY ANALYSIS IN ECOLOGY. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4663-4_4
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