Anselin, L.1980: Estimation methods for spatial autoregressive structures. Regional Science Dissertations and Monograph Series 8. Ithaca, NY: Cornell University.
2.
Aspinall, R.J.1994: Exploratory spatial analysis in GIS: generating geographical hypotheses from spatial data. In Worboys, M.F., editor, Innovations in GIS 1, London: Taylor and Francis, 139–147.
3.
Bayes, T.1763: An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society, 330–418.
4.
Bennett, R.J.1985: A reappraisal of the role of spatial science and statistical inference in geography in Britain. Espace Geographique14, 23–28.
5.
Berger, J.O.2000: Bayesian analysis: a look at today and thoughts of tomorrow. Journal of the American Statistical Association95, 1269–1276.
6.
Berk, R.A., Western, B. and Weiss, R.E.1995a: Statistical inference for apparent populations. Sociological Methodology25, 421–458.
7.
Berk, R.A., Western, B. and Weiss, R.E.1995b: Reply to Bollen, Firebaugh, and Rubin. Sociological Methodology25, 481–485.
8.
Berliner, L.M. 2000: Hierarchical Bayesian modeling in the environmental sciences. Allegemeines Statisches Archiv (Journal of the German Statistical Society) 84, 141–53.
9.
Besag, J. and Green, P.J.1993: Spatial statistics and Bayesian computation. Journal of the Royal Statistics Society, Series B (Methodological)55, 25–37.
10.
Besag, J. and Newell, J.1991: The detection of clusters in rare diseases. Journal of the Royal Statistical Society, Series A154, 143–155.
11.
Best, N.G., Arnold, R.A., Thomas, A., Waller, L.A. and Conlon, E.M.1999: Bayesian models for spatially correlated disease and exposure data. Bayesian Statistics6, 131–156.
12.
Biggeri, A. and Marchi, M.1995: Case control designs for the detection of spatial clusters of diseases. Environmetrics6, 385–393.
13.
Bollen, K.A.1995: Apparent and nonapparent significance tests. Sociological Methodology25, 459–468.
14.
Bryk, A.S. and Raudenbush, S.W.1992: Hierarchical linear models. Newbury Park, CA: Sage.
15.
Cappe, O. and Robert, C.P.2000: Markov Chain Monte Carlo: 10 years and still running!, Journal of the American Statistical Association95, 1282–1286.
16.
Carlin, B.P. and Lewis, T.A.1996: Bayes and empirical Bayes methods for data analysis. New York: Chapman and Hall.
17.
Carlin, B.P. and Lewis, T.A.2000: Empirical Bayes: past, present and future. Journal of the American Statistical Association95, 1286–1289.
18.
Chao, H.P. and Peck, S.1999: A decision model for environmental R and D. Environment International25, 871–886.
19.
Christakos, G.2001: Modern spatiotemporal geostatistics. Oxford: Oxford University Press.
20.
Christakos, G. and Li, X.1998: Bayesian maximum entropy analysis and mapping: a farewell to kriging estimators?Mathematical Geology30, 435–462.
21.
Congdon, P.1997: Multilevel and clustering analysis of health outcomes in small areas. European Journal of Population13, 305–338.
22.
Congdon, P.2000a: A Bayesian approach to prediction using the gravity model, with an application to patient flow modeling. Geographical Analysis32, 205–224.
23.
Congdon, P.2000b: Monitoring suicide mortality: a Bayesian approach. European Journal of Population16, 251–284.
24.
Congdon, P.2001a: Bayesian statistical modeling. New York: John Wiley.
25.
Congdon, P.2001b: Health status and healthy life measures for population health need assessment: modelling variability and uncertainty. Health and Place7, 13–25.
26.
Congdon, P., Smith, A. and Dean, C.1998: Assessing psychiatric morbidity from community registers: methods for Bayesian adjustment. Urban Studies35, 2323–2352.
27.
Cressie, N.1989: Empirical Bayes estimation of undercount in the Decennial census. Journal of the American Statistical Association84, 1033–1044.
Cressie, N., Stern, H.S. and Wright, D.R.2000: Mapping rates associated with polygons. Journal of Geographical Systems2, 61–69.
30.
Devine, O.J., Louis, T.A. and Halloran, M.E.1996: Identifying areas with elevated disease incidence rates using empirical Bayes estimators. Geographical Analysis28, 187–199.
31.
Dua, P. and Ray, S.C.1995: A BVAR model for the Connecticut economy. Journal of Forecasting14, 167–180.
32.
Fernandez, C. and Steel, M.F.J.1999: Reference priors for the general location-scale model. Statistics and Probability Letters43, 377–384.
33.
Firebaugh, G.1995: Will Bayesian inference help?. Sociological Methodology25, 469–472.
34.
Fischer, A.J., Arnold, A.J. and Gibbs, M.1996: Information and the speed of innovation adoption. American Journal of Agricultural Economics78, 1073–1081.
35.
Fotheringham, A.S., Brunsdon, C. and Charlton, M.2000: Quantitative geography: perspectives on spatial data analysis. London: Sage Publications.
36.
Frenkel, A.2000: Can regional policy affect firms' innovation potential in lagging regions?Annals of Regional Science34, 315–341.
37.
Garcia-Ferrer, A., Highfield, R.A., Palm, F. and Zellner, A.1987: Macroeconomic forecasting using pooled international data. Journal of Business and Economic Statistics5, 53–68.
38.
Gelman, A. and Rubin, D.B.1995: Discussion: avoiding model selection in Bayesian social research. Sociological Methodology25, 165–173.
39.
Gelman, A. and Rubin, D.B.1999: Evaluating and using statistical method in the social sciences: a discussion of ‘A critique of the Bayesian information criterion for model selection’. Sociological Methods and Research27, 403–410.
40.
Gelman, A., Carlin, J., Stern, H. and Rubin, D.B.1995: Bayesian data analysis. London: Chapman and Hall.
41.
Ghatak, A.1998: Vector autoregression modelling and forecasting growth of South Korea. Journal of Applied Statistics25, 579–592.
42.
Gorbey, S., James, D. and Poot, J.1999: Population forecasting with endogenous migration: an application to trans-Tasman migration. International Regional Science Review22, 69–101.
43.
Greenland, S.2000a: Principles of multilevel modelling. International Journal of Epidemiology29, 158–167.
44.
Greenland, S.2000b: When should epidemiologic regressions use random coefficients?Biometrics56, 915–921.
45.
Gupta, R.C., Albanese, R.A., Penn, J.W. and White, T.J.1997: Bayesian estimation of relative risk in biomedical research. Environmetrics8, 133–143.
46.
Heckerman, D.1996: A tutorial on learning with Bayesian networks. Technical Report MSR-TR-95-06. Microsoft Research, Advanced Technology Division, Microsoft Corporation, One Microsoft Way, Redmond, WA 98052, USA.
47.
Heckerman, D.1997: Bayesian networks for data mining. Data Mining and Knowledge Discovery1, 79–119.
48.
Hepple, L.W.1979: Bayesian analysis of the linear model with spatial dependence. In Bartels, C.P.A. and Ketellaper, R.H., editors, Exploratory and explanatory statistical analysis of spatial data, The Hague: Martinus Nijhoff, 179–199.
49.
Hepple, L.W.1995a: Bayesian techniques in spatial and network econometrics: l. Model comparison and posterior odds. Environment and Planning A27, 447–469.
50.
Hepple, L.W.1995b: Bayesian techniques in spatial and network econometrics: 2. Computational methods and algorithms. Environment and Planning A27, 615–644.
51.
Hoeting, J.A., Madigan, D., Raftery, A.E. and Volinsky, C.T.1999: Bayesian model averaging: a tutorial. Statistical Science14, 4–35.
52.
Hoff, K.1997: Bayesian learning in an infant industry model. Journal of International Economics43, 409–436.
53.
Ickstadt, K. and Wolpert, R.L.1999: Spatial regression for marked point processes. Bayesian Statistics6, 323–341.
54.
Ickstadt, K., Wolpert, R.L. and Lu, X.1998: Modeling travel demand in Portland, Oregon. In Rey, D., Muller, P. and Sinha, D., editors, Practical nonparametric and semiparametric Bayesian statistics, New York: Springer-Verlag, 305–322.
55.
Jackman, S.2000: Estimation and inference via Bayesian simulation: an introduction to Markov Chain Monte Carlo. American Journal of Political Science44, 375–404.
56.
Jeffreys, H.1935: Some tests of significance, treated by the theory of probability. Proceedings of the Cambridge Philosophical Society31, 203–222.
57.
Jeffreys, H.1961: Theory of probability(third edition). London: Oxford University Press.
58.
Jones, K.1997: Multilevel approached to modelling contextuality: from nuisance to substance in the analysis of voting behavior. In Westert, G.P. and Verhoeff, R.N., editors, Places and people: multilevel modelling in geographic research, Nederlandse Geografische Studies 227, The Royal Dutch Geographical Society, 19–43.
59.
Jordan, P., Brubacher, D., Tsugane, S., Tsubono, Y., Gey, K.F. and Moser, U.1997: Modelling of mortality data from a multi-centre study in Japan by means of Poisson regression with error in variables. International Journal of Epidemiology26, 501–507.
60.
King, G.1997: A solution to the ecological inference problem: reconstructing individual behavior from aggregate data. Princeton, NJ: Princeton University Press.
61.
King, G., Rosen, O. and Tanner, M.A.1999: Binomial-beta hierarchical models for ecological inference. Sociological Methods and Research28, 61–89.
62.
Kreft, I. and DeLeeuw, J.1998: Introducing multilevel modeling. London: Sage Publications.
63.
LaPlace, P.S.1812: Theorie analytique des probabilites. Paris: Courcier.
64.
Le, N.D. and Zidek, J.V.1992: Interpolation with uncertain spatial coverage: a Bayesian alternative to kriging. Journal of Multivariate Analysis43, 351–374.
65.
Le, N.D., Sun, W. and Zidek, J.V.1997: Bayesian multivariate spatial interpolation with data missing-by-design. Journal of the Royal Statistical Society, Series B59, 501–510.
66.
Leamer, E.E.1978: Specification searches: ad hoc inference with nonexperimental data. New York: John Wiley.
67.
LeSage, J.P.1997: Bayesian estimation of spatial autoregressive models. International Regional Science Review20, 113–129.
LeSage, J.P. and Krivelyova, A.1999: A spatial prior for Bayesian vector autoregressive models. Journal of Regional Science39, 297–317.
70.
LeSage, J.P. and Magura, M.1988: A regional payroll forecasting model that uses Bayesian shrinkage techniques for data pooling. Regional Science Perspectives19, 100–113.
71.
LeSage, J.P.1991: Using interindustry input-output relations as a Bayesian prior in employment forecast models. International Journal of Forecasting7, 231–238.
72.
LeSage, J.P. and Pan, Z.1995: Using spatial contiguity as Bayesian prior information in regional forecasting models. International Regional Science Review18, 33–54.
73.
Lewis, D. and Anderson, R.1999: Residential real estate brokerage efficiency and the implications of franchising: a Bayesian approach. Real Estate Economics27, 543–560.
74.
Lewis, S.M. and Raftery, A.E.1999: Bayesian analysis of event history models with unobserved heterogeneity via Markov Chain Monte Carlo: application to the explanation of fertility decline. Sociological Methods and Research28, 35–60.
75.
Litterman, R.B.1986: A statistical approach to economic forecasting. Journal of Business and Economic Statistics4, 1–4.
76.
Magura, M.1987: The use of input-output tables in specifying interindustry and interregional labor market linkages. Papers of the Regional Science Association62, 117–123.
77.
Magura, M.1990: Using input-output data in a Bayesian vector autoregressive forecasting model. In Anselin, L. and Madden, M., editors, New directions in regional analysis, London: Bellhaven Press, 133–145.
78.
Magura, M.1998: IO and spatial information as Bayesian priors in an employment forecasting model. Annals of Regional Science32, 495–503.
79.
Marden, J.I.2000: Hypothesis testing: from p values to Bayes factors. Journal of the American Statistical Association95, 1316–1319.
80.
Marshall, R.J.1991: A review of methods for the statistical analysis of spatial pattern of disease. Journal of the Royal Statistical Society, Series A154, 421–441.
81.
McAllister, M.K. and Kirkwood, G.P.1998: Using Bayesian decision analysis to help achieve a precautionary approach for managing developing fisheries. Canadian Journal of Fisheries and Aquatic Sciences55, 2642–2661.
82.
Mugglin, A.S. and Carlin, B.P.1998: Hierarchical modeling in geographic information systems. Journal of Agricultural, Biological, and Environmental Sciences3, 111–130.
83.
Mugglin, A.S., Carlin, B.P., Zhu, L. and Conlon, E.1999: Bayesian areal interpolation, estimation, and smoothing: an inferential approach for geographic information systems. Environment and Planning A31, 1337–1352.
84.
Mur, J.1999: Testing for spatial autocorrelation: moving average versus autoregressive processes. Environment and Planning A31, 1371–1382.
85.
Murphy, M. and Wang, D.2001: Do previous birth interval and mother's education influence infant survival?Population Studies55, 37–47.
86.
Nandram, B., Sedransk, J. and Pickle, L.W.2000.Bayesian analysis and mapping of mortality rates for chronic obstructive pulmonary disease. Journal of the American Statistical Association95,1110–1118.
87.
Ouwersloot, H. and Rietveld, P.2000: The geography of R and D: tobit analysis and a Bayesian approach to mapping R and D activities in the Netherlands. Environment and Planning A32, 1673–1688.
88.
Peterman, R.M. and Anderson, J.L.1999: Decision analysis: a method for taking uncertainties into account in risk-based decision making. Human and Ecological Risk Assessment5, 231–244.
89.
Phillips, L.D.1974: Bayesian statistics for social scientists. New York: Thomas Y. Crowell Company.
90.
Pringle, D.G.1996: Mapping disease risk estimates based on small numbers: an assessment of empirical Bayes techniques. Economic and Social Review27, 341–363.
91.
Puri, A. and Soydemir, G.2000: Forecasting industrial employment figures in southern California: a Bayesian vector autoregressive model. Annals of Regional Science34, 503–514.
92.
Qian S.S., Lavine, M. and Stow, C.A.2000: Univariate Bayesian nonparametric binary regression with application in environmental management. Environmental and Ecological Statistics7, 77–91.
93.
Raftery, A.E.1986: A note on Bayes factors for log-linear contingency table models with vague prior information. Journal of the Royal Statistical Society, Series B48, 429–450.
94.
Raftery, A.E.1995a: Bayesian model selection in social research. Sociological Methodology25, 111–163.
95.
Raftery, A.E.1995b: Rejoinder: model selection is unavoidable in social research. Sociological Methodology25, 1185–1195.
96.
Raftery, A.E.1999: Bayes factors and BIC: comment on ‘A critique of the Bayesian information criterion for model selection’. Sociological Methods and Research27, 411–427.
97.
Rindskopf, D.1998: Null-hypothesis tests are not completely stupid, but Bayesian statistics are better. Behavioral and Brain Sciences21, 215–222.
98.
Rubin, D.B.1995: Bayes, Neyman, and calibration. Sociological Methodology25, 473–479.
99.
Schwarz, G.1978: Estimating the dimension of a model. Annals of Statistics6: 461–464.
100.
Shampine, A.1998: Compensating for information externalities in technology diffusion models. American Journal of Agricultural Economics80, 337–346.
101.
Spiegelhalter, D.J., Thomas, A. and Best, N.G.1999: WinBUGS version 1.2 user manual. Cambridge: MRC Biostatistics Unit.
102.
Stern, H.S. and Cressie, N.2000: Posterior predictive model checks for disease mapping models. Statistics in Medicine19, 2377–2397.
103.
Sun, W., Le, N.D., Zidek, J.V. and Burnett, R.1998: Assessment of a Bayesian multivariate interpolation approach for health impact studies. Environmetrics9, 565–586.
104.
Tanner, M.A.1996: Tools for statistical inference: methods for the exploration of posterior distributions and likelihood functions(third edition). New York: Springer-Verlag.
105.
Varis, O. and Kuikka, S.1999: Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management. Ecological Modelling119, 177–195.
106.
von Neumann, J. and Morgenstern, O.1944: Theory of games and economic behavior. Princeton, NJ: Princeton University Press.
107.
Wakefield, J.C. and Morris, S.E.2001: The Bayesian modeling of disease risk in relation to a point source. Journal of the American Statistical Association96, 77–91.
108.
Waller, L., Carlin, B., Hong, X. and Gelfand, A.1997: Hierarchical spatio-temporal mapping of disease rates. Journal of the American Statistical Association92, 607–617.
109.
Weakliem, D.L.1999: A critique of the Bayesian information criterion for model selection. Sociological Methods and Research27, 359–397.
110.
Western, B.1999: Bayesian analysis for sociologists: an introduction. Sociological Methods and Research28, 7–34.
111.
Western, B.2001: Bayesian thinking about macro-sociology. The American Journal of Sociology107, 353–378.
112.
Withers, S.D.2001: Quantitative methods: advancement in ecological inference. Progress in Human Geography25, 87–96.
113.
Zellner, A.1971: An introduction to Bayesian inference in econometrics. New York: John Wiley.