Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility-Reference-Cited by-同舟云学术

Optimal nonparametric testing of Missing Completely At Random and its connections to compatibility

Published:2023-10-01 Issue:5 Volume:51 Page:
ISSN:0090-5364
Container-title:The Annals of Statistics
language:
Short-container-title:Ann. Statist.

Author:

Berrett Thomas B.¹,Samworth Richard J.²

Affiliation:

1. Department of Statistics, University of Warwick

2. Statistical Laboratory, Centre for Mathematical Sciences

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference59 articles.

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2. ZHU, Z., WANG, T. and SAMWORTH, R. J. (2022). High-dimensional principal component analysis with heterogeneous missingness. J. R. Stat. Soc. Ser. B. Stat. Methodol. 84 2000–2031.

3. LI, J. and YU, Y. (2015). A nonparametric test of missing completely at random for incomplete multivariate data. Psychometrika 80 707–726.

4. SPOHN, M.-L., NÄF, J., MICHEL, L. and MEINSHAUSEN, N. (2021). PKLM: A flexible MCAR test using classification. ArXiv preprint. Available at arXiv:2109.10150.

5. Little, R. J. A. and Rubin, D. B. (2002). Statistical Analysis with Missing Data, 2nd ed. Wiley Series in Probability and Statistics. Wiley, Hoboken, NJ.

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