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Weighted least squares fitting using ordinary least squares algorithms

Citations

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Cited by:

  1. Qing Li & Long Hai Vo, 2021. "Intangible Capital and Innovation: An Empirical Analysis of Vietnamese Enterprises," Economics Discussion / Working Papers 21-02, The University of Western Australia, Department of Economics.
  2. Joost Ginkel & Pieter Kroonenberg, 2014. "Using Generalized Procrustes Analysis for Multiple Imputation in Principal Component Analysis," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 242-269, July.
  3. Husson, François & Josse, Julie & Saporta, Gilbert, 2016. "Jan de Leeuw and the French School of Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 73(i06).
  4. de Leeuw, Jan, 2006. "Principal component analysis of binary data by iterated singular value decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 21-39, January.
  5. Chan, Tak-Shing T. & Gibberd, Alex, 2025. "Feasible model-based principal component analysis: Joint estimation of rank and error covariance matrix," Computational Statistics & Data Analysis, Elsevier, vol. 201(C).
  6. Qing Li & Long Hai Vo, 2024. "Determinants of intangible capital investment in Vietnam: A firm‐level analysis," The World Economy, Wiley Blackwell, vol. 47(3), pages 1055-1088, March.
  7. Julie Josse & Jérôme Pagès & François Husson, 2011. "Multiple imputation in principal component analysis," 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. 5(3), pages 231-246, October.
  8. Jose Giovany Babativa-Márquez & José Luis Vicente-Villardón, 2021. "Logistic Biplot by Conjugate Gradient Algorithms and Iterated SVD," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
  9. Kiers, Henk A. L., 2002. "Setting up alternating least squares and iterative majorization algorithms for solving various matrix optimization problems," Computational Statistics & Data Analysis, Elsevier, vol. 41(1), pages 157-170, November.
  10. Valter Cesar de Souza & Sergio Augusto Rodrigues & Luís Roberto Almeida Gabriel Filho, 2024. "Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-20, December.
  11. Schoonees, P.C. & Groenen, P.J.F. & van de Velden, M., 2015. "Least-squares Bilinear Clustering of Three-way Data," Econometric Institute Research Papers EI2014-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  12. Josse, Julie & Husson, François, 2012. "Selecting the number of components in principal component analysis using cross-validation approximations," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1869-1879.
  13. Mohammad Naim Azimi, 2016. "Assessing the Exchange Rate Volatility as an External Shock to Chinese Economy," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(5), pages 277-285, May.
  14. Wasito, Ito & Mirkin, Boris, 2006. "Nearest neighbours in least-squares data imputation algorithms with different missing patterns," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 926-949, February.
  15. Namgil Lee & Jong-Min Kim, 2018. "Block tensor train decomposition for missing data estimation," Statistical Papers, Springer, vol. 59(4), pages 1283-1305, December.
  16. Zhu, Ziwei & Wang, Tengyao & Samworth, Richard J., 2022. "High-dimensional principal component analysis with heterogeneous missingness," LSE Research Online Documents on Economics 117647, London School of Economics and Political Science, LSE Library.
  17. Michailidis, George & De Leeuw, Jan, 2005. "Homogeneity analysis using absolute deviations," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 587-603, March.
  18. Julie Josse & Marie Chavent & Benot Liquet & François Husson, 2012. "Handling Missing Values with Regularized Iterative Multiple Correspondence Analysis," Journal of Classification, Springer;The Classification Society, vol. 29(1), pages 91-116, April.
  19. Groenen, P.J.F. & Giaquinto, P. & Kiers, H.A.L., 2003. "Weighted Majorization Algorithms for Weighted Least Squares Decomposition Models," Econometric Institute Research Papers EI 2003-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  20. Josse, Julie & Husson, François, 2016. "missMDA: A Package for Handling Missing Values in Multivariate Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i01).
  21. Sébastien Loisel & Yoshio Takane, 2019. "Comparisons among several methods for handling missing data in principal component analysis (PCA)," 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. 13(2), pages 495-518, June.
  22. Marcon, Arthur & Ribeiro, José Luis Duarte & Olteanu, Yasmin & Fichter, Klaus, 2024. "How the interplay between innovation ecosystems and market contingency factors impacts startup innovation," Technology in Society, Elsevier, vol. 76(C).
  23. A. Iodice D’Enza & A. Markos & F. Palumbo, 2022. "Chunk-wise regularised PCA-based imputation of missing data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 365-386, June.
  24. Camila Kolling & José Luis Duarte Ribeiro & Donato Morea & Gianpaolo Iazzolino, 2023. "Corporate social responsibility and circular economy from the perspective of consumers: A cross‐cultural analysis in the cosmetic industry," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(3), pages 1226-1243, May.
  25. Ziwei Zhu & Tengyao Wang & Richard J. Samworth, 2022. "High‐dimensional principal component analysis with heterogeneous missingness," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 2000-2031, November.
  26. Unkel, S. & Trendafilov, N.T., 2010. "A majorization algorithm for simultaneous parameter estimation in robust exploratory factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3348-3358, December.
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