accmv - Inference with Available Complete-Case Missing Values
Implements inverse probability weighted, regression adjustment, and multiply robust estimators under the available complete-case missing value assumption of Cheng, Chen, Smith, and Zhao (2022) <doi:10.48550/arXiv.2207.02289>. Supports one or two primary variables, exponential-tilt sensitivity analysis, regression weights, and nonparametric bootstrap confidence intervals.
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ipwmissing-datamnarpythonstatistics
2.70 scoredebiasedInference - Bootstrap Inference with Debiased Nonparametric Estimators
Implements debiased kernel density and local-linear regression estimators with empirical-bootstrap simultaneous confidence bands, as proposed by Cheng and Chen (2019) <doi:10.1214/19-EJS1575>. Also provides bandwidth selectors and grid-based confidence sets for density level sets and inverse regression.
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bootstrapconfidence-bandskernel-density-estimationnonparametric-statisticspython
2.70 score