Nothing
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 |
|
|---|---|
| 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 |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.