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Two new algorithms for estimating the parameters of a latent class model for ordered categorical data with polytomous responses are introduced based on a newly defined regularized Laplacian matrix derived from the response matrix.
A spectral clustering approach, termed Spectral Clustering for Mixed Membership, based on an ideal cone structure of the variant for the eigendecomposition of the regularized Laplacian matrix is proposed, which shows the asymptotic consistency of the algorithm under mild assumptions by providing error bounds for the in...
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