Confidence Intervals for l_k,p,θ Distances

Distance predicting functions have a number of uses when objects in space can be represented as points. When a predicted distance between two points is determined by a distance predicting function, the unknown distance between the points may be overestimated or underestimated due to the statistical nature of distance predicting functions. Since an analyst may desire a measure of the accuracy of the predicted distance, we have developed a procedure for calculating confidence intervals for unknown distances. The procedure utilizes information that is provided by the sample Pearson coefficients.