Nearest neighbours in least-squares data imputation algorithms with different missing patterns
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- Hunt, Lynette & Jorgensen, Murray, 2003. "Mixture model clustering for mixed data with missing information," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 429-440, January.
- Michael E. Tipping & Christopher M. Bishop, 1999. "Probabilistic Principal Component Analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 611-622.
- Henk Kiers, 1997. "Weighted least squares fitting using ordinary least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 251-266, June.
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Cited by:
- Michael Ziegelmeyer, 2013.
"Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey,"
AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 49-76, January.
- Ziegelmeyer, Michael, 2011. "Illuminate the unknown: Evaluation of imputation procedures based on the SAVE Survey," MEA discussion paper series 11235, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
- Huei-Wen Teng & Wen-Liang Hung & Yen-Ju Chao, 2015. "Bayesian Markov chain Monte Carlo imputation for the transiting exoplanets with an application in clustering analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 1120-1132, May.
- Coppi, Renato & Gil, Maria A. & Kiers, Henk A.L., 2006. "The fuzzy approach to statistical analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 1-14, November.
- Mark Chiang & Boris Mirkin, 2010. "Intelligent Choice of the Number of Clusters in K-Means Clustering: An Experimental Study with Different Cluster Spreads," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 3-40, March.
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