Finney minimum variance unbiased estimator described by Aitcheson and Brown.24 The Krige method using 4 minimum variance unbiased estimator is optimal under the assumption of lognormal distribution (Aitchison and Brown 34 p- 44). The shift parameter, tT, is calculated using Krige's quantile formula.?? The tT is involved in the log-transform as log (x, -T), where X; are measurement values in pCi/gm and may be negative and below the minimum detectable activity (MDA). The param- eter removes problems of taking logrithms of negative numbers and improves the approximation to the lognormal probability density function. computer algorithm calculates the first T. Figure 8, The T = 0.6 pCi/cn, exhibits an example where the left MDA concentrations are forced more closely to a straight line than the same data with T = o (Fig. 7) using the Krige method?? to adjust this parameter about the first approximation to maximize the r-test value. The means and variances arc calculated using the Finney fifteen term eapproximetion to 4 mininun variance estimate (Aitchison and Brown, 24 Eq. 5.37). A visual inspec- tion of each data set is done by a log-probability plot (examples on Figs. 4 to 10). For comparison, using the quantile method.2* the mean and variance was estimated The minimus variance log-probability-line was used to find the quantile values. Numerical approximations to the cumulative normai distribution used formulas 26.2.23 and 26.2.22 in Abromowitz and Stegun's handboc::.49 the comparison of methods Tables 45 through 47 illustrate for 24) bry which have severa] and 137¢5 at the same sample location. For 24. an, censored values, the arithmetic mean frequently underestimates the Krige method (average of 30 percent, , underestimation range: 0 to -100 percent, 0-15 cm soils), but the 40 - a so11114