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Linear regression in astronomy. IIA wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
Document ID
19930026437
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Feigelson, Eric D.
(NASA Headquarters Washington, DC United States)
Babu, Gutti J.
(Pennsylvania State Univ. University Park, United States)
Date Acquired
August 15, 2013
Publication Date
September 20, 1992
Publication Information
Publication: Astrophysical Journal, Part 1
Volume: 397
Issue: 1
ISSN: 0004-637X
Subject Category
Astronomy
Accession Number
93A10434
Funding Number(s)
CONTRACT_GRANT: NAGW-1917
CONTRACT_GRANT: NSF DMS-90-07717
CONTRACT_GRANT: NAGW-2120
Distribution Limits
Public
Copyright
Other

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