Efficient estimation of generalized linear latent variable models
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DOI: 10.1371/journal.pone.0216129
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Cited by:
- Robin Fuchs & Denys Pommeret & Cinzia Viroli, 2022. "Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 31-53, March.
- Jenni Niku & Francis K. C. Hui & Sara Taskinen & David I. Warton, 2021. "Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
- Francis K.C. Hui & Nicole A. Hill & A.H. Welsh, 2022. "Assuming independence in spatial latent variable models: Consequences and implications of misspecification," Biometrics, The International Biometric Society, vol. 78(1), pages 85-99, March.
- Riki Herliansyah & Ruth King & Stuart King, 2022. "Laplace Approximations for Capture–Recapture Models in the Presence of Individual Heterogeneity," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 401-418, September.
- Ting Fung Ma & Fangfang Wang & Jun Zhu, 2023. "On generalized latent factor modeling and inference for high‐dimensional binomial data," Biometrics, The International Biometric Society, vol. 79(3), pages 2311-2320, September.
- Andersson, Björn & Jin, Shaobo & Zhang, Maoxin, 2023. "Fast estimation of multiple group generalized linear latent variable models for categorical observed variables," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
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