Prediction precision is arguably the most relevant criterion of a model in practice and is often a sought after property. A common difficulty with covariates measured with errors is the impossibility of performing prediction evaluation on the data even if a model is completely given without any unknown parameters. We bypass this inherent difficulty by using special properties on moment relation...

resolution of binary mixtures of theophylline (theo), montelukast (mkst) and loratadine (lora) with minimum sample pretreatment and without analyte separation has been successfully achieved by multivariate spectrophotometric calibration, together with partial least-squares (pls-1), principal component regression (pcr) and hybrid linear analysis (hla). data of analysis were obtained from uv–vis ...

In this paper, we present an efficient methodology for the evaluation of cylindricity error. Based on the proposed methodology, the cylindricity error can be assessed using any of the existing criteria (LSC, MCC, MIC or MRS). The results indicate that the proposed procedure is fast and the results it provides are very accurate.