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A novel bias-bound approach for non-parametric inference is introduced, focusing on both density and conditional expectation estimation. It constructs valid confidence intervals that account for the presence of a non-negligible bias and thus make it possible to perform inference with optimal mean squared error minimizing bandwidths. This package is based on Schennach (2020) <doi:10.1093/restud/rdz065>.
Package details |
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Author | Xinyu DAI [aut, cre], Susanne M Schennach [aut] |
Maintainer | Xinyu DAI <xinyu_dai@brown.edu> |
License | GPL (>= 3) |
Version | 0.3.0 |
URL | https://doi.org/10.1093/restud/rdz065 |
Package repository | View on CRAN |
Installation |
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