lpme: Nonparametric Estimation of Measurement Error Models
Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method. See Huang and Zhou (2017) <doi:10.1080/10485252.2017.1303060>, Zhou and Huang (2016) <doi:10.1214/16-EJS1210>, Huang and Zhou (2020) <doi:10.1214/20-EJS1688>, and Zhou and Huang (2019) <doi:10.1080/03610918.2017.1402044>.
| Version: |
1.1.3 |
| Depends: |
R (≥ 3.0.2) |
| Imports: |
Rcpp (≥ 0.11.1), decon, flexmix, splines, locpol |
| LinkingTo: |
Rcpp, RcppArmadillo (≥ 0.4.300.0) |
| Published: |
2022-05-09 |
| Author: |
Haiming Zhou [aut, cre, cph],
Xianzheng Huang [aut] |
| Maintainer: |
Haiming Zhou <haiming2019 at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Citation: |
lpme citation info |
| CRAN checks: |
lpme results |
Documentation:
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