Lawrence Berkeley National Laboratory

Our motivation in this work is to find an adequate probability distribution to fit sales volumes ofdifferent appliances. This distribution allows for the translation of sales rank into sales volume.This paper shows that the log-normal distribution and specifically the truncated version are well suited for this purpose. We demonstrate that using sales proxies derived from a calibratedtruncated log-normal distribution function can be used to produce realistic estimates of marketaverage product prices, and product attributes. We show that the market averages calculated with the sales proxies derived from the calibrated, truncated log-normal distribution provide better market average estimates than sales proxies estimated with simpler distribution functions.