PCA model building with missing data: New proposals and a comparative study

Chemometrics and Intelligent Laboratory Systems

Volumn 146, Issue , 2015, Pages 77-88

  Folch Fortuny, A ^a   Arteaga, F ^b   Ferrer, A ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSIDAD CATÓLICA DE VALENCIA SAN VICENTE MÁRTIR   (Spain)

Author keywords

Missing data; PCA model building; PCA model exploitation

Indexed keywords

DIESEL FUEL; OLIVE OIL;

ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; COMPARATIVE STUDY; CONTROLLED STUDY; DATA AUGMENTATION METHOD; DATA EXTRACTION; ITERATIVE ALGORITHM; KNOWN DATA REGRESSION; KNOWN DATA REGRESSION WITH PARTIAL LEAST SQUARES REGRESSION; KNOWN DATA REGRESSION WITH PRINCIPAL COMPONENT REGRESSION; MATHEMATICAL ANALYSIS; MEAN SQUARED PREDICTION ERROR; NONLINEAR ITERATIVE PARTIAL LEAST SQUARES; NONLINEAR PROGRAMMING APPROACH; PARTIAL LEAST SQUARES REGRESSION; PREDICTOR VARIABLE; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROJECTION TO THE MODEL PLANE; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL CONCEPTS; STATISTICAL MODEL; TRIMMED SCORES REGRESSION;

EID: 84929578031     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2015.05.006     Document Type: Article

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