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Automatic dimensionality selection from the scree plot via the use of profile likelihood

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Cited by:

  1. Leule M. Hailemariam & Denamo A. Nuramo, 2023. "Examining Challenges in Complying with the Principles of Sustainability for the Design of Urban Bridges in Ethiopia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
  2. José M. Maisog & Andrew T. DeMarco & Karthik Devarajan & Stanley Young & Paul Fogel & George Luta, 2021. "Assessing Methods for Evaluating the Number of Components in Non-Negative Matrix Factorization," Mathematics, MDPI, vol. 9(22), pages 1-13, November.
  3. Angelo Mele & Lingxin Hao & Joshua Cape & Carey E. Priebe, 2019. "Spectral inference for large Stochastic Blockmodels with nodal covariates," Papers 1908.06438, arXiv.org, revised Mar 2021.
  4. Arno de Caigny & Kristof Coussement & Koen W. de Bock & Stefan Lessmann, 2019. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," Post-Print hal-02275958, HAL.
  5. Ting Dai & Adam Davey, 2023. "Determining Dimensionality with Dichotomous Variables: A Monte Carlo Simulation Study and Applications to Missing Data in Longitudinal Research," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
  6. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
  7. Sancar Adali & Carey E. Priebe, 2016. "Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities," Journal of Classification, Springer;The Classification Society, vol. 33(3), pages 485-506, October.
  8. Noroozi, Majid & Pensky, Marianna, 2024. "Sparse subspace clustering in diverse multiplex network model," Journal of Multivariate Analysis, Elsevier, vol. 203(C).
  9. Shin Ji-Hyung & Infante-Rivard Claire & Graham Jinko & McNeney Brad, 2012. "Adjusting for Spurious Gene-by-Environment Interaction Using Case-Parent Triads," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(2), pages 1-23, January.
  10. Chen, Guodong & Arroyo, Jesús & Athreya, Avanti & Cape, Joshua & Vogelstein, Joshua T. & Park, Youngser & White, Chris & Larson, Jonathan & Yang, Weiwei & Priebe, Carey E., 2025. "Multiple network embedding for anomaly detection in time series of graphs," Computational Statistics & Data Analysis, Elsevier, vol. 203(C).
  11. Mullally, Conner & Chakravarty, Shourish, 2018. "Are matching funds for smallholder irrigation money well spent?," Food Policy, Elsevier, vol. 76(C), pages 70-80.
  12. Borchert, Philipp & Coussement, Kristof & De Caigny, Arno & De Weerdt, Jochen, 2023. "Extending business failure prediction models with textual website content using deep learning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 348-357.
  13. repec:osf:osfxxx:ek4n3_v1 is not listed on IDEAS
  14. Shen, Cencheng & Sun, Ming & Tang, Minh & Priebe, Carey E., 2014. "Generalized canonical correlation analysis for classification," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 310-322.
  15. Nan Wei & Changjun Li & Jiehao Duan & Jinyuan Liu & Fanhua Zeng, 2019. "Daily Natural Gas Load Forecasting Based on a Hybrid Deep Learning Model," Energies, MDPI, vol. 12(2), pages 1-15, January.
  16. Ronaldo F. Zampolo & Frederico H. R. Lopes & Rodrigo M. S. de Oliveira & Martim F. Fernandes & Victor Dmitriev, 2024. "Dimensionality Reduction and Clustering Strategies for Label Propagation in Partial Discharge Data Sets," Energies, MDPI, vol. 17(23), pages 1-18, November.
  17. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan, 2020. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1563-1578.
  18. Shieh Albert D & Hung Yeung Sam, 2009. "Detecting Outlier Samples in Microarray Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-26, February.
  19. repec:osf:socarx:x5vmz_v1 is not listed on IDEAS
  20. Zhiliang Ma & Adam Cardinal-Stakenas & Youngser Park & Michael Trosset & Carey Priebe, 2010. "Dimensionality Reduction on the Cartesian Product of Embeddings of Multiple Dissimilarity Matrices," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 307-321, November.
  21. Zhao, Yuxuan & Matteson, David S. & Mostofsky, Stewart H. & Nebel, Mary Beth & Risk, Benjamin B., 2022. "Group linear non-Gaussian component analysis with applications to neuroimaging," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
  22. Hutchison, Paul D. & Daigle, Ronald J. & George, Benjamin, 2018. "Application of latent semantic analysis in AIS academic research," International Journal of Accounting Information Systems, Elsevier, vol. 31(C), pages 83-96.
  23. Patrick Rubin‐Delanchy & Joshua Cape & Minh Tang & Carey E. Priebe, 2022. "A statistical interpretation of spectral embedding: The generalised random dot product graph," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1446-1473, September.
  24. Saxena, Ayushi & Lyzinski, Vince, 2025. "Lost in the shuffle: Testing power in the presence of errorful network vertex labels," Computational Statistics & Data Analysis, Elsevier, vol. 204(C).
  25. Chung, Jaewon & Bridgeford, Eric & Arroyo, Jesus & Pedigo, Benjamin D. & Saad-Eldin, Ali & Gopalakrishnan, Vivek & Xiang, Liang & Priebe, Carey E. & Vogelstein, Joshua T., 2020. "Statistical Connectomics," OSF Preprints ek4n3, Center for Open Science.
  26. Yoder, Jordan & Chen, Li & Pao, Henry & Bridgeford, Eric & Levin, Keith & Fishkind, Donniell E. & Priebe, Carey & Lyzinski, Vince, 2020. "Vertex nomination: The canonical sampling and the extended spectral nomination schemes," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
  27. Vainora, J., 2024. "Latent Position-Based Modeling of Parameter Heterogeneity," Cambridge Working Papers in Economics 2455, Faculty of Economics, University of Cambridge.
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