Information loss due to incomplete data from a spatial gaussian one-parameter first-order conditional process

Bibliography

• Besag , J. 1977 . Efficiency of pseudolikelihood estimation for simple Gaussian fields . Biometrika , 64 : 616 – 618 .
   Web of Science ®Google Scholar
• Besag , J. and Moran , P.A.P. 1975 . On the estimation and testing of spatial interaction in Gaussian lattice processes . Biometrika , 62 : 555 – 562 .
   Web of Science ®Google Scholar
• Haining R. Griffith D. Bennett R. Maximum likelihood estimation with missing spatial data and with an application to remotely sensed data. Comm Statist. -Theor. Meth 1989 to appear
   Google Scholar
• Mardia , K.V. and Marshall , R.J. 1984 . Maximum likelihood estimation of models for residual covariance in spatial regression . Biometrika , 71 : 135 – 146 .
   Web of Science ®Google Scholar
• Martin , R.J. 1984 . Exact maximum likelihood for incomplete data from a correlated Gaussian process . Comm. Statist. -Theor. Meth , 13 : 1275 – 1288 .
   Web of Science ®Google Scholar
• Martin , R.J. 1987 . Some comments on correction techniques for boundary effects and missing value techniques . Geog. Anal , 19 : 273 – 282 .
   Web of Science ®Google Scholar
• Orchard , T. and Woodbury , M.A. A missing information principle: theory and applications . Proceedings of the 6th Berkeley Symposium . Edited by: Le Cam , L.M. and Neyman , J. Vol. 1 , pp. 697 – 715 . Berkeley : University of California Press .
   Google Scholar