APPROXIMATE LOCAL CONFIDENCE-INTERVALS UNDER CHANGE OF SUPPORT

Approximate local confidence intervals are constructed from uncertaint y models in the form of the conditional distribution of the random var iable Z given values of variables [Z(i), i = 1,..., n]. When the suppo rt of the variable Z is any support other than that of the data, the c onditional distributions require a change of support correction. This paper investigates the effect of change of support on the approximate local confidence intervals constructed by cumulative indicator kriging , class indicator kriging, and probability kriging under a variety of conditions. The conditions are generated by three simulated deposits w ith grade distributions of successively higher degree of skewness; a p oint support and two different block supports are considered. The pape r also compares the confidence intervals obtained from these methods u sing the most used measures of confidence interval effectiveness.