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Latent structureMultivariate analysis

Robust Latent Profile Analysis

Robust latent profile analysis identificerer latente undergrupper af individer baseret på deres kontinuerlige multivariate indikatorer, samtidig med at parameterestimater beskyttes mod forvrængning fra outliers eller atypiske observationer. Metoden udvider standard latent profile analysis ved at erstatte de Gaussiske komponentdensiteter med alternativer med tungere haler eller kontaminerede normalfordelinger, som nedvægter ekstreme tilfælde under estimering.

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Kilder

  1. Vermunt, J. K. & Magidson, J. (2002). Latent class cluster analysis. In J. A. Hagenaars & A. L. McCutcheon (Eds.), Applied Latent Class Analysis (pp. 89–106). Cambridge University Press. ISBN: 978-0521594035
  2. Punzo, A. & McNicholas, P. D. (2016). Robust clustering in regression analysis via the contaminated Gaussian cluster-weighted model. Journal of Classification, 33(2), 293–331. DOI: 10.1007/s00357-017-9234-x

Sådan citerer du denne side

ScholarGate. (2026, June 3). Robust Latent Profile Analysis. ScholarGate. https://scholargate.app/da/statistics/robust-latent-profile-analysis

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ScholarGateRobust Latent Profile Analysis (Robust Latent Profile Analysis). Hentet 2026-06-15 fra https://scholargate.app/da/statistics/robust-latent-profile-analysis · Datasæt: https://doi.org/10.5281/zenodo.20539026