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MVC app: A smartphone application for performing chemometric methods

Parastar, H ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1016/j.chemolab.2015.08.010
  3. Publisher: Elsevier , 2015
  4. Abstract:
  5. In this work, a novel smartphone application entitled ". MVC app" is developed to perform different multivariate calibration methods. This app is designed for chemists who are not expert in programming or in advanced statistics. The developed application can use any Android-powered device as an environment for running. It is an easy to use app which can simply install in your smartphone and play. Different multivariate calibration methods, such as multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) are included in this app. As an instance, for performing PLS modeling, first calibration and validation data sets are imported (via USB or Wi-Fi). Then, the number of latent variables (LVs) is chosen using leave-one-out cross-validation (LOO-CV). Afterwards, PLS model is built and the user can review the modeling results. In this regard, figures of merit (FOMs) of models, such as root-mean square error of prediction (RMSEP), standard error of prediction (SEP), bias and relative error (RE) and other parameters can be viewed for each analyte. Furthermore, various plotting options are included for each model. All of these options are available just by touching the screen, with no complexity that almost every chemist can use
  6. Keywords:
  7. Android ; Multiple linear regression ; Multivariate calibration ; Partial least squares ; Principal component regression ; Smartphone ; Analytical error ; Calibration ; Chemometric analysis ; Computer interface ; Computer program ; Equipment design ; Mobile application ; Multiple linear regression analysis ; Partial least squares regression ; Play ; Principal component analysis ; Priority journal ; Statistical analysis ; Structural equation modeling
  8. Source: Chemometrics and Intelligent Laboratory Systems ; Volume 147 , October , 2015 , Pages 105-110 ; 01697439 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0169743915002014