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:Sebastian Calonico <[email protected]>, Matias D. Cattaneo <[email protected]>, Max H. Farrell <[email protected]>

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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.32 score 1 stars 2 packages 35 scripts 423 downloads 1 mentions 5 exports 30 dependencies

Last updated 4 years agofrom:f0e199f210. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-linux-x86_64NOTENov 23 2024

Exports:kdbwselectkdrobustlpbwselectlprobustnprobust.plot

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr