Package: SpatialRoMLE 0.1.1.1

SpatialRoMLE: Robust Maximum Likelihood Estimation for Spatial Error Model

Provides robust estimation for spatial error model to presence of outliers in the residuals. The classical estimation methods can be influenced by the presence of outliers in the data. We proposed a robust estimation approach based on the robustified likelihood equations for spatial error model (Vural Yildirim & Yeliz Mert Kantar (2020): Robust estimation approach for spatial error model, Journal of Statistical Computation and Simulation, <doi:10.1080/00949655.2020.1740223>).

Authors:Vural Yildirim [aut, cre], Yeliz Mert Kantar [aut, ths]

SpatialRoMLE_0.1.1.1.tar.gz
SpatialRoMLE_0.1.1.1.zip(r-4.7)SpatialRoMLE_0.1.1.1.zip(r-4.6)SpatialRoMLE_0.1.1.1.zip(r-4.5)
SpatialRoMLE_0.1.1.1.tgz(r-4.6-any)SpatialRoMLE_0.1.1.1.tgz(r-4.5-any)
SpatialRoMLE_0.1.1.1.tar.gz(r-4.7-any)SpatialRoMLE_0.1.1.1.tar.gz(r-4.6-any)
SpatialRoMLE_0.1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SpatialRoMLE/json (API)

# Install 'SpatialRoMLE' in R:
install.packages('SpatialRoMLE', repos = c('https://wyilldirim.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/wyilldirim/spatialromle/issues

Datasets:

On CRAN:

Conda:

2.70 score 214 downloads 1 exports 0 dependencies

Last updated from:c84b4bf610. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK86
source / vignettesOK148
linux-release-x86_64OK94
macos-release-arm64OK138
macos-oldrel-arm64OK153
windows-develOK65
windows-releaseOK65
windows-oldrelOK94
wasm-releaseOK88

Exports:RoMLE.error

Dependencies: