Principal components analysis of spectral data. I - Methodology for spectral classification

Details Principal components analysis of spectral data. I - Methodology for spectral classification Principal components analysis of spectral data. I - Methodology for spectral classification

Mar 1983

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1983a%26as...51..443w&link_type=abstract

Astronomy and Astrophysics Supplement Series, vol. 51, Mar. 1983, p. 443-461.

Astronomy and Astrophysics

Astrophysics

26

Astronomical Photometry, Classifications, Multivariate Statistical Analysis, Spectrum Analysis, Stellar Spectra, A Stars, Correlation Coefficients, Data Reduction, Error Analysis, Tables (Data)

Scientific paper

Principal components analysis is applied to published narrow-band photometric data on 53 standard stars of spectral types A and F. Correlations within the data are displayed and the propagation of errors is discussed. Techniques for improving the precision and the efficiency of the classification are explored, including non-linear regression and trimming and grouping of the original data. As an example, a set of 47 observed variables is reduced to 3, with no loss of precision.

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