restrSigmaGPCM computes constrained covariance matrices for the 14 GPCM specifications
Sigma=restrSigmaGPCM(SigmaB, niini, pa, nocheck)
exampleSigma=restrSigmaGPCM(SigmaB, niini, pa, nocheck, lmd)
exampleSigma=restrSigmaGPCM(SigmaB, niini, pa, nocheck, lmd, OMG)
example[Sigma, lmd]=restrSigmaGPCM(___)
example[Sigma, lmd, OMG]=restrSigmaGPCM(___)
example[Sigma, lmd, OMG, GAM]=restrSigmaGPCM(___)
exampleThis routine applies the constraints to the covariance matrices using the specifications contained in input structure pa.
Use of restrSigmaGPCM with just one output argument.Sigma
=restrSigmaGPCM(SigmaB
,
niini
,
pa
,
nocheck
)
Use of restrSigmaGPCM with all default options.Sigma
=restrSigmaGPCM(SigmaB
,
niini
,
pa
,
nocheck
,
lmd
)
Garcia-Escudero L.A., Mayo-Iscar, A. and Riani M. (2020). Model-based clustering with determinant-and-shape constraint, Statistics and Computing, vol. 30, pp. 1363–1380, https://link.springer.com/article/10.1007/s11222-020-09950-w
Garcia-Escudero L.A., Mayo-Iscar, A. and Riani M. (2022). Constrained parsimonious model-based clustering, Statistics and Computing, vol. 32, https://doi.org/10.1007/s11222-021-10061-3