In this article, the parameric decomposition method is considered as a technique for batch correction using three process primaries. It is proved that the parameric decomposition technique using optimal process primaries is a suitable method for reliable batch correction. Besides, the evaluation of parameric correction error for estimation of metamerism index is discussed. The creation of optimal spectral dataset to derive the appropriate process primaries is presented and the estimation of optimal statistical colorants for color reproduction of paint system is also developed. A set of pigments as primaries is used to generate three sets of batches using Kubelka-Munk theory; each set includes 10,000 paramer samples. Three sets of batches are generated to have different distributions around the match sample of target. The performance of process primaries derived from the Munsell dataset is compared with the optimal estimated statistical colorants for reliable parameric correction. To achieve greater success in estimation of appropriate metamerism index and make the estimated index more reliable, the statistical colorants used for parameric correction should be achieved from the spectral dataset generated by real primaries being used for matching of the target color. The outcome of parameric correction for pairs having miscellaneous mismatches is investigated to find out if it is sensible to just consider mismatch threshold for pairs being corrected. Finally, the conceptual subject of paramerism is developed to verify which spectral essence could be called as the paramer of an individual target color being matched. (C) 2010 Wiley Periodicals, Inc. Col Res Appl, 36, 437-448, 2011; Published online 12 November 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/col.20642