Publication detail

Outliers detection in the statistical accuracy test of a stability constants prediction

MELOUN, M. BRODOVSKÁ, S. KUPKA, K.

English title

Outliers detection in the statistical accuracy test of a stability constants prediction

Type

Peer-reviewed article not indexed in WoS or Scopus

Language

en

Original abstract

The regression diagnostics algorithm REGDIA in S-Plus is introduced to examine the accuracy of pK a predicted with four programs: PALLAS, MARVIN, PERRIN and SYBYL. On basis of a statistical analysis of residuals, outlier diagnostics are proposed. Residual analysis of the ADSTAT program is based on examining goodness-of-fit via graphical diagnostics of 15 exploratory data analysis plots, such as bar plots, box-and-whisker plots, dot plots, midsum plots, symmetry plots, kurtosis plots, differential quantile plots, quantile-box plots, frequency polygons, histograms, quantile plots, quantile-quantile plots, rankit plots, scatter plots, and autocorrelation plots.

Keywords in English

pKa prediction, Dissociation constants, Outliers, Residuals, Goodness of fit, Williams graph

Released

2010-02-01

Publisher

Springer

ISSN

0259-9791

Journal

JOURNAL OF MATHEMATICAL CHEMISTRY

Volume

47

Number

2

Pages from–to

891–909

Pages count

19

BIBTEX


@article{BUT51012,
  author="Milan {Meloun} and Sylva {Brodovská} and Karel {Kupka}",
  title="Outliers detection in the statistical accuracy test of a stability constants prediction",
  journal="JOURNAL OF MATHEMATICAL CHEMISTRY",
  year="2010",
  volume="47",
  number="2",
  pages="891--909",
  issn="0259-9791"
}