Generalization of pair correlation method (PCM) for non-parametric variable selection

Journal of Chemometrics

Volumn 16, Issue 8-10, 2002, Pages 436-443

  Héberger, Károly ^a   Rajkó, Róbert ^b  

^a CHEMICAL RESEARCH CENTER   (Hungary)

^b UNIVERSITY OF SZEGED   (Hungary)

Author keywords

Non parametric variable and or model selection; Pair correlation method

Indexed keywords

CORRELATION METHODS; RANDOM PROCESSES;

GENERALISATION; MODEL SELECTION; NON-PARAMETRIC VARIABLE AND/OR MODEL SELECTION; NONPARAMETRICS; PAIR-CORRELATION METHOD; PARAMETRIC VARIABLES; PREDICTOR VARIABLES; VARIABLE FACTORS; VARIABLE MODEL; VARIABLES SELECTIONS;

STATISTICAL TESTS;

COMPARATIVE STUDY; CONFERENCE PAPER; CONTINGENCY TABLE; CORRELATION ANALYSIS; MODEL; NONPARAMETRIC TEST; PREDICTION; SCORING SYSTEM;

EID: 0036685021     PISSN: 08869383     EISSN: None     Source Type: Journal    
DOI: 10.1002/cem.748     Document Type: Conference Paper

References (28)

1. Elimination of uninformative variables for multivariate calibration
2. Selection of variables in multiple regression: Part I. Review and evaluation
3. Selection of variables in multiple regression: Part II. Chosen procedures, computations and examples
4. Selection of variables to preserve multivariate data structure, using principal components
5. Interactive variables selection (IVS) for PLS. Part I. Theory and algorithms
6. Interactive variables selection (IVS) for PLS. Part II. Chemical applications
7. Single and domain mode variable selection in 3D QSAR applications
8. Selecting factors for partial least squares
9. Variable and subset selection in PLS regression
10. Genetic algorithms as a tool for wavelength selection in multivariate calibration
11. Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: Application to near-infrared spectroscopy
12. Genetic algorithms applied to feature selection in PLS regression: How and when to use them
13. The use of neural networks for variable selection in QSAR
14. Variable selection for neural networks in multivariate calibration
15. Neural network studies. 3. Variables selection in the cascade-correlation learning architecture
16. Partial order ranking-based QSARs: Estimation of solubilities and octanol-water partitioning
17. Discrimination of statistically equivalent variables in quantitative structure-activity relationships
18. Conditional Fisher's exact test as a selection criterion for pair-correlation method. Type I and type II errors
19. Projection pursuit regression
20. Sliced inverse regression for dimension reduction
21. Nonparametric regression applied to quantitative structure-activity relationships
22. Comparison of chemometric methods for prediction of rate constants and activation energies of radical addition reactions
23. Evaluation of polarity indicators and stationary phases by principal component analysis in gas-liquid chromatography
24. 3D-modelling and prediction by WHIM descriptors. Part 6. Application of WHIM descriptors in QSAR studies