Missing data

Imputation, estimation despite etc



Placeholder to remind me to read Morvan et al. (2021).

References

Blackwell, Matthew, James Honaker, and Gary King. 2015. “A Unified Approach to Measurement Error and Missing Data: Details and Extensions.” Sociological Methods & Research, June, 0049124115589052. https://doi.org/10.1177/0049124115589052.
———. 2015. “A Unified Approach to Measurement Error and Missing Data: Details and Extensions.” Sociological Methods & Research, June, 0049124115589052. https://doi.org/10.1177/0049124115589052.
Clark, James S., and Ottar N. Bjørnstad. 2004. “Population Time Series: Process Variability, Observation Errors, Missing Values, Lags, and Hidden States.” Ecology 85 (11): 3140–50. https://doi.org/10.1890/03-0520.
Dempster, A. P., N. M. Laird, and D. B. Rubin. 1977. “Maximum Likelihood from Incomplete Data Via the EM Algorithm.” Journal of the Royal Statistical Society: Series B (Methodological) 39 (1): 1–22. https://doi.org/10.1111/j.2517-6161.1977.tb01600.x.
Kennedy, Edward H., Jacqueline A. Mauro, Michael J. Daniels, Natalie Burns, and Dylan S. Small. 2019. “Handling Missing Data in Instrumental Variable Methods for Causal Inference.” Annual Review of Statistics and Its Application 6 (1): 125–48. https://doi.org/10.1146/annurev-statistics-031017-100353.
Mohan, Karthika, and Judea Pearl. 2018. “Consistent Estimation Given Missing Data.” In International Conference on Probabilistic Graphical Models, 284–95. http://proceedings.mlr.press/v72/mohan18a.html.
Mohan, Karthika, Judea Pearl, and Jin Tian. 2013. “Graphical Models for Inference with Missing Data.” In Advances in Neural Information Processing Systems, 1277–85. http://papers.nips.cc/paper/4899-gra.
Morvan, Marine Le, Julie Josse, Erwan Scornet, and Gaël Varoquaux. 2021. “What’s a Good Imputation to Predict with Missing Values?” arXiv:2106.00311 [cs, Stat], June. http://arxiv.org/abs/2106.00311.
Rubin, Donald B. 1987. “The Calculation of Posterior Distributions by Data Augmentation: Comment: A Noniterative Sampling/Importance Resampling Alternative to the Data Augmentation Algorithm for Creating a Few Imputations When Fractions of Missing Information Are Modest: The SIR Algorithm.” Journal of the American Statistical Association 82 (398): 543–46. https://doi.org/10.2307/2289460.
Shpitser, Ilya, Karthika Mohan, and Judea Pearl. 2015. “Missing Data as a Causal and Probabilistic Problem.” http://ftp.cs.ucla.edu/pub/stat_ser/r454.pdf.
Tu, Ruibo, Cheng Zhang, Paul Ackermann, Hedvig Kjellström, and Kun Zhang. 2018. “Causal Discovery in the Presence of Missing Data.” arXiv:1807.04010 [cs, Stat], July. http://arxiv.org/abs/1807.04010.

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