title: Envirometrics. Part I: Modeling of water salinity and air quality data.
abstract: Envirometrics utilises advanced mathematical, statistical and information tools to extract information. Two typical environmental data sets are analysed using MVATOB (Multi Variate Analysis TOol Box). The first data set corresponds to the variable river salinity. Least median squares (LMS) detected the outliers whereas linear least squares (LLS) could not detect and remove the outliers. The second data set consists of daily readings of air quality values. Outliers are detected by LMS and unbiased regression coefficients are estimated by multi-linear regression (MLR). As explanatory variables are not independent, principal component regression (PCR) and partial least squares regression (PLSR) are used. Both examples demonstrate the superiority of LMS over LLS.
authors.affiliation: Pharmaceutical Department, Physical Chemistry Section, University of Parma, I-43100 Parma, Italy. braiban@unipr.it
authors.forename: A
authors.initials: A
authors.lastname: Braibanti
authors.forename: N R
authors.initials: NR
authors.lastname: Gollapalli
authors.forename: S B
authors.initials: SB
authors.lastname: Jonnalagaddaj
authors.forename: S
authors.initials: S
authors.lastname: Duvvuru
authors.forename: S R
authors.initials: SR
authors.lastname: Rupenaguntla
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods; D005618:Fresh Water / Q000032:analysis; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D015999:Multivariate Analysis; D009518:New York; D009657:North Carolina; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D014874:Water Pollutants, Chemical