Abstract
This paper demonstrates how some recently developed graphical diagnostic techniques can be used to explore and improve the specification of logistic oil exploration models. Techniques are applied to information on 124 hydrocarbon exploration wells drilled between 1948 and 1963 into the ‘B’ Division of the Mississippian (Osage Series) in a 13 by 13 square mile area of Stafford County, south-central Kansas.
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Agterberg, F. P., 1974, Automatic contouring of geological maps to detect target areas for mineral exploration: Math. Geol., v. 6, p. 373–394
Agterberg, F. P., 1984, Trend surface analysis,in G. L. Gaile and C. J. Willmott (Eds.), Spatial statistics and models: Reidel Publishing Co., Dordrecht, Holland, p. 147–171.
Baker, R. J. and Nelder, J. A., 1978, The GLIM system: release 3: Numerical Algorithms Group, Oxford, England, 189 p.
Baxter, M., 1985, Quasi-likelihood estimation and diagnostic statistics for spatial interaction models: Environ. Plann. A, v. 17, p. 1627–1635.
Belsley, D. A., Kuh, E., and Welsch, R. E., 1980, Regression diagnostics: John Wiley & Sons, New York, 292 p.
Chesher, A., 1985, Smoothing logit partial residual plots: University of Bristol, Department of Economics Discussion Paper No. 85/164, 7 p.
Chung, C. F., 1978, Computer program for the logistic model to estimate the probability of occurrence of discrete events: Geological Survey of Canada, Paper 78-11, Ottawa, 23 p.
Chung, C. F. and Agterberg, F. P., 1980, Regression models for estimating mineral resources from geological map data: Math. Geol., v. 12, p. 473–488.
Cleveland, W. S., 1979, Robust locally weighted regression and smoothing scatterplots: Jour. Amer. Stat. Assoc., v. 74, p. 829–836.
Cleveland, W. S. and McGill, R., 1984, The many faces of a scatterplot: Jour. Amer. Stat. Assoc., v. 79, p. 807–822.
Cook, R. D. and Weisberg, S., 1982a, Residuals and influence in regression: Chapman and Hall, London, 230 p.
Cook, R. D. and Weisberg, S., 1982b, Criticism and influence analysis in regression,in S. Leinhardt (Ed.), Sociological methodology 1982: Jossey-Bass, San Francisco, p. 313–361.
Cox, D. R., 1970, The analysis of binary data: Methuen, London, 139 p.
Cox, N. J. and Jones, K., 1981, Exploratory data analysis,in N. Wrigley and R. J. Bennett (Eds.), Quantitative geography: a British view: Routledge and Kegan Paul, London, p. 135–143.
Doveton, J. H., 1973, Numerical analysis relating location of hydrocarbon traps to structure and stratigraphy of the Mississippian ‘B’ of Stafford County, South-Central Kansas: Technical Report, KOX Project, Geological Research Section, Kansas Geological Survey, 56 p.
Dunn, R., Longley, P. A., and Wrigley, N., 1986, Graphical procedures for identifying functional form in binary discrete choice models: A case study of revealed tenure choice: Reg. Sci. Urban Econ.
Harbaugh, J. W., Doveton, J. H., and Davis, J. C., 1977, Probability methods in oil exploration: John Wiley & Sons, New York, 269 p.
Hoaglin, D. C. and Welsch, R. E., 1978, The hat matrix in regression and ANOVA: Amer. Statist., v. 32, p. 17–22.
Jones, K., 1984, Graphical methods for exploring relationships,in G. Bahrenberg, M. M. Fischer, and P. Nijkamp (Eds.), Recent developments in spatial analysis: methodology, measurement, models: Gower, Aldershot, p. 215–227.
Landwehr, J. M., Pregibon, D., and Shoemaker, A. C., 1984, Graphical methods for assessing logistic regression models: Jour. Amer. Stat. Assoc., v. 79, p. 61–71.
Larsen, W. A. and McCleary, S. J., 1972, The use of partial residual plots in regression analysis: Technometrics, v. 14, p. 781–790.
McCullagh, P. and Nelder, J. A., 1983, Generalised linear models: Chapman and Hall, London, 261 p.
McFadden, D., 1979, Quantitative methods for analysing travel behavior of individuals: some recent developments,in D. A. Hensher and P. R. Stopher (Eds.), Behavioral travel modelling: Croom Helm, London, p. 279–318.
Nelder, J. A. and Wedderburn, R. W. M., 1972, Generalised linear models: Jour. Roy Stat. Soc. Ser. A, v. 135, p. 370–384.
Pregibon, D., 1981, Logistic regression diagnostics: Ann. Stat., v. 9, p. 705–724.
Pregibon, D., 1982, Resistant fits of some commonly used logistic models with medical applications: Biometrics, v. 38, p. 485–498.
Ryan, T. A., Joiner, B. L., and Ryan, B. F., 1982, Minitab reference manual: Pennsylvania State University Press, Pennsylvania, 154 p.
Velleman, P. F. and Welsch, R. E., 1981, Efficient computing of regression diagnostics: Amer. Statist., v. 35, p. 234–241.
Weisberg, S., 1980, Applied linear regression: John Wiley & Sons, New York, 283 p.
Wrigley, N., 1983, Quantitative methods: on data and diagnostics: Prog. Hum. Geog., v. 7, p. 565–575.
Wrigley, N., 1984, Quantitative methods: diagnostics revisited: Prog. Hum. Geog., v. 8, p. 525–535.
Wrigley, N., 1985, Categorical data analysis for geographers and environmental scientists: Longman, London, 392 p.
Wrigley, N. and Dunn, R., 1984, Diagnostics and resistant fits in logit choice models,in D. E. Pitfield (Ed.), London papers in regional science, vol. 14, Discrete choice models in regional science: Pion, London, p. 44–66.
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Wrigley, N., Dunn, R. Graphical diagnostics for logistic oil exploration models. Math Geol 18, 355–374 (1986). https://doi.org/10.1007/BF00906061
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DOI: https://doi.org/10.1007/BF00906061