Envirometrics. Part I: Modeling of water salinity and air quality data

Envirometrics utilises advanced mathematical, statistical and information t ools to extract information. Two typical environmental data sets are analys ed using MVATOB (Multi Variate Analysis TOol Box). The first data set corre sponds 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 qualit y values. Outliers are detected by LMS and unbiased regression coefficients are estimated by multi-linear regression (MLR). As explanatory variables a re not independent, principal component regression (PCR) and partial least squares regression (PLSR) are used. Both examples demonstrate the superiori ty of LMS over LLS.