Package: nprobust 0.4.0
Sebastian Calonico
nprobust: Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation
Tools for data-driven statistical analysis using local polynomial regression and kernel density estimation methods as described in Calonico, Cattaneo and Farrell (2018, <doi:10.1080/01621459.2017.1285776>): lprobust() for local polynomial point estimation and robust bias-corrected inference, lpbwselect() for local polynomial bandwidth selection, kdrobust() for kernel density point estimation and robust bias-corrected inference, kdbwselect() for kernel density bandwidth selection, and nprobust.plot() for plotting results. The main methodological and numerical features of this package are described in Calonico, Cattaneo and Farrell (2019, <doi:10.18637/jss.v091.i08>).
Authors:
nprobust_0.4.0.tar.gz
nprobust_0.4.0.tar.gz(r-4.5-noble)nprobust_0.4.0.tar.gz(r-4.4-noble)
nprobust_0.4.0.tgz(r-4.4-emscripten)nprobust_0.4.0.tgz(r-4.3-emscripten)
nprobust.pdf |nprobust.html✨
nprobust/json (API)
# Install 'nprobust' in R: |
install.packages('nprobust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:f0e199f210. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 23 2024 |
R-4.5-linux-x86_64 | NOTE | Dec 23 2024 |
Exports:kdbwselectkdrobustlpbwselectlprobustnprobust.plot
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr