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dawai: An R Package for Discriminant Analysis with Additional Information

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  • Conde, David
  • Fernández, Miguel
  • Salvador, Bonifacio
  • Rueda, Cristina

Abstract

The incorporation of additional information into discriminant rules is receiving increasing attention as the rules including this information perform better than the usual rules. In this paper we introduce an R package called dawai, which provides the functions that allow to define the rules that take into account this additional information expressed in terms of restrictions on the means, to classify the samples and to evaluate the accuracy of the results. Moreover, in this paper we extend the results and definitions given in previous papers (Fernández, Rueda, and Salvador 2006, Conde, Fernández, Rueda, and Salvador 2012, Conde, Salvador, Rueda, and Fernández 2013) to the case of unequal covariances among the populations, and consequently define the corresponding restricted quadratic discriminant rules. We also define estimators of the accuracy of the rules for the general more than two populations case. The wide range of applications of these procedures is illustrated with two data sets from two different fields, i.e., biology and pattern recognition.

Suggested Citation

  • Conde, David & Fernández, Miguel & Salvador, Bonifacio & Rueda, Cristina, 2015. "dawai: An R Package for Discriminant Analysis with Additional Information," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 66(i10).
    • Handle: RePEc:jss:jstsof:v:066:i10
    DOI: http://hdl.handle.net/10.18637/jss.v066.i10
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    References listed on IDEAS

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    1. Borra, Simone & Di Ciaccio, Agostino, 2010. "Measuring the prediction error. A comparison of cross-validation, bootstrap and covariance penalty methods," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2976-2989, December.
    2. Rueda, Cristina & Fernández, Miguel A. & Peddada, Shyamal Das, 2009. "Estimation of Parameters Subject to Order Restrictions on a Circle With Application to Estimation of Phase Angles of Cell Cycle Genes," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 338-347.
    3. Barragán, Sandra & Fernández, Miguel & Rueda, Cristina & Peddada, Shyamal, 2013. "isocir: An R Package for Constrained Inference Using Isotonic Regression for Circular Data, with an Application to Cell Biology," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i04).
    4. Fernandez, Miguel A. & Rueda, Cristina & Salvador, Bonifacio, 2006. "Incorporating Additional Information to Normal Linear Discriminant Rules," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 569-577, June.
    5. El Barmi, Hammou & Johnson, Matthew & Mukerjee, Hari, 2010. "Estimating cumulative incidence functions when the life distributions are constrained," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 1903-1909, October.
    6. Ori Davidov & Shyamal Peddada, 2013. "Testing for the Multivariate Stochastic Order among Ordered Experimental Groups with Application to Dose–Response Studies," Biometrics, The International Biometric Society, vol. 69(4), pages 982-990, December.
    7. Kim, Ji-Hyun, 2009. "Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3735-3745, September.
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    1. David Conde & Miguel A. Fernández & Cristina Rueda & Bonifacio Salvador, 2021. "Isotonic boosting classification rules," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(2), pages 289-313, June.

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