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It is common in geographic modelling to use a one-parameter spatial model to specify the&#13; inverse covariance matrix in terms of I-bW, for some known matrix W. Exact Gaussian maximum&#13; likelihood estimation of b requires evaluation of the determinant of the covariance matrix. For large&#13; data sets, this evaluation of the determinant can be slow and good approximations can be useful.&#13; Seventy regional configurations are used to consider some approximations to the determinant of I-bW&#13; that are fast to evaluate, and their usefulness is compared

Some Fast Methods for Fitting Some One-parameter Spatial Models