Determining the number of components in mixtures of linear models

By Dollena S. Hawkins, D. M. Allen, Arnold J. Stromberg. 2001

106 citations recorded by the source corpus.

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How collinearity affects mixture regression results (2015, background): “Reverting to prior studies (e.g., Claeskens and Hart 2009; Hawkins et al. 2001) allows us to identify and select nine information criteria (i.”
Fitting mixtures of linear regressions (2010, unknown): “[8] studied the problem of determining the”
Heuristic Optimization Methods in Econometrics (2009, background): “Hawkins et al. (2001) use differential evolution for a similar problem.”
Underlying Structure of Ruminative Thinking: Factor Analysis of the Ruminative Thought Style Questionnaire (2013, methodology): “Velicer’s minimum average partial (MAP) test (Velicer 1976) and Horn’s parallel analysis (Horn 1965) were also undertaken using syntax proposed by O’Connor (2000).”
A review of recent approaches for capturing heterogeneity in partial least squares path modelling (2008, unknown): “These are well-known from finite mixture model literature and their performance has been discussed in several simulation studies in different context, such as mixture regression models (Hawkins et al., 2001; Andrews and Currim, 2003b; Sarstedt and Schwaiger, 2007, 2008), mixture logit models (Andrew”
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002 (2008, methodology): “The MAIC (Modified Akaike Info Criterion) falls in-between (for a detailed description, see Hawkins et al. 2001 ).”