ISSN:
1573-8868
Keywords:
Coefficient of variation
;
sampling error
;
serial correlation
;
spectral analysis
;
uranium
Source:
Springer Online Journal Archives 1860-2000
Topics:
Geosciences
,
Mathematics
Notes:
Abstract This paper describes a statistical analysis of reconnaissance exploration geochemical data for uranium. Three sets of data were analyzed, as they related to: (a) Charlotte-Winston-Salem and (b) Charlotte two-degree NTMS quadrangles of the south-eastern U.S.A. The coefficient of variation for uranium in each of the three sets of data was less than unity and hence no transformation of the original variable was needed. These data were subjected to correlogram analysis. A first-order Markovian model of the type: Y0 exp (-a |p|) was fit by the least-squares method to serial correlation coefficients of these data using the method proposed by Deming (1948). The model was tested by computing the variance-volume relationship for assumed individual blocks of unit length. The noise in the input (record) was eliminated by the application of an optimum bilateral exponential smoothing technique developed by Agterberg. A comparison of spectral density estimates obtained by a maximum entropy method employing Yule-Walker equations and the Burg algorithm was also made. The prediction error coefficients needed to determine the order of the autoregressive process and hence the spectral densities were determined in both cases for the three sets of data.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01035242
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