Package: L1pack 0.41-245
L1pack: Routines for L1 Estimation
L1 estimation for linear regression using Barrodale and Roberts' method <doi:10.1145/355616.361024> and the EM algorithm <doi:10.1023/A:1020759012226>. Estimation of mean and covariance matrix using the multivariate Laplace distribution, density, distribution function, quantile function and random number generation for univariate and multivariate Laplace distribution <doi:10.1080/03610929808832115>.
Authors:
L1pack_0.41-245.tar.gz
L1pack_0.41-245.zip(r-4.5)L1pack_0.41-245.zip(r-4.4)L1pack_0.41-245.zip(r-4.3)
L1pack_0.41-245.tgz(r-4.4-x86_64)L1pack_0.41-245.tgz(r-4.4-arm64)L1pack_0.41-245.tgz(r-4.3-x86_64)L1pack_0.41-245.tgz(r-4.3-arm64)
L1pack_0.41-245.tar.gz(r-4.5-noble)L1pack_0.41-245.tar.gz(r-4.4-noble)
L1pack_0.41-245.tgz(r-4.4-emscripten)L1pack_0.41-245.tgz(r-4.3-emscripten)
L1pack.pdf |L1pack.html✨
L1pack/json (API)
| # Install 'L1pack' in R: |
| install.packages('L1pack', repos = c('https://faosorios.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/faosorios/l1pack/issues
- ereturns - Excess returns for Martin Marietta and American Can companies
Last updated 7 months agofrom:60e126997b. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 21 2024 |
| R-4.5-win-x86_64 | OK | Oct 22 2024 |
| R-4.5-linux-x86_64 | OK | Oct 22 2024 |
| R-4.4-win-x86_64 | OK | Nov 21 2024 |
| R-4.4-mac-x86_64 | OK | Nov 21 2024 |
| R-4.4-mac-aarch64 | OK | Nov 21 2024 |
| R-4.3-win-x86_64 | OK | Nov 21 2024 |
| R-4.3-mac-x86_64 | OK | Nov 21 2024 |
| R-4.3-mac-aarch64 | OK | Nov 21 2024 |
Exports:dlaplacedmLaplacel1fitladlad.fitlad.fit.BRlad.fit.EMLaplaceFitplaplaceqlaplacerlaplacermLaplacesimulate.ladWH.Laplace
Dependencies:fastmatrix
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence intervals from 'lad' models | confint.lad |
| Excess returns for Martin Marietta and American Can companies | ereturns |
| Minimum absolute residual (L1) regression | l1fit |
| Least absolute deviations regression | lad |
| Fitter functions for least absolute deviation (LAD) regression | lad.fit |
| Fit a least absolute deviation (LAD) regression model | lad.fit.BR lad.fit.EM |
| The symmetric Laplace distribution | dlaplace Laplace plaplace qlaplace rlaplace |
| Estimation of mean and covariance using the multivariate Laplace distribution | LaplaceFit |
| Multivariate Laplace distribution | dmLaplace mLaplace rmLaplace |
| Simulate responses from 'lad' models | simulate.lad |
| Calculate variance-covariance matrix from 'lad' models | vcov.lad |
| Wilson-Hilferty transformation | WH.Laplace |
