  This paper introduces two methods for estimating reliable prediction
intervals for local linear least-squares regressions, named Bounded Oscillation
Prediction Intervals (BOPI). It also proposes a new measure for comparing
interval prediction models named Equivalent Gaussian Standard Deviation (EGSD).
The experimental results compare BOPI to other methods using coverage
probability, Mean Interval Size and the introduced EGSD measure. The results
were generally in favor of the BOPI on considered benchmark regression
datasets. It also, reports simulation studies validating the BOPI method's
reliability.
