Understanding and controlling rotations in factor analytic models
By P. Paatero, Philip K. Hopke, Xin-Hua Song, Ziad Ramadan. 2002
429 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/7b370338b5e51258a3b0b5a19145e786f3099b43
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Romà Tauler
- A. de Juan
- Steven G. Brown
- S. Eberly
- P. Paatero
- M. Maeder
- Qi Zhang
- G. Norris
Citations in the corpus
- Methods for estimating uncertainty in factor analytic solutions (2013, background): “The problem of rotations has been discussed in Paatero et al. (2002) and recently in more detail in Paatero and Hopke (2009).”
- Understanding atmospheric organic aerosols via factor analysis of aerosol mass spectrometry: a review (2011, background): “Then the expected value of Q (Qexp) should equal the degrees of freedom of the fitted data [54]:”
- Review of receptor modeling methods for source apportionment (2016, unknown): “This problem is termed rotational ambiguity (Paatero et al., 2002; Paatero and Hopke, 2009).”
- Assessing positive matrix factorization model fit: a new method to estimate uncertainty and bias in factor contributions at the measurement time scale (2008, unknown): “PMF2 has numerous optimization parameters that can be set by the user, and methods of choosing these values have been published elsewhere (Paatero, 2000; Paatero et al., 2002, 2005).”
- Multiset Data Analysis: Extended Multivariate Curve Resolution (2020, background): “This type of constraint contributes significantly to the elimination of rotation ambiguities, because of the presence of zero values in factor Ck and Sl T matrices, which allows in many circumstances for the achievement of unique resolution conditions, as stated by Rolf Manne’s resolution theorems(1”
- Methods for estimating uncertainty in PMF solutions: examples with ambient air and water quality data and guidance on reporting PMF results. (2015, background): “The modest BS-DISP results with four factors suggest that there is some factor interdependence and rotational ambiguity, confirmed by the oblique, slanting edges seen in the G-space plots (Paatero et al., 2002, 2005).”