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-any)SpatialRoMLE_0.1.1.1.zip(r-4.6-any)SpatialRoMLE_0.1.1.1.zip(r-4.5-any)
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✨
DESCRIPTION
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 209 downloads 1 exports 0 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK88
source / vignettesOK148
linux-releaseOK80
macos-releaseOK167
macos-oldrelOK148
windows-develOK59
windows-releaseOK55
windows-oldrelOK50
wasm-releaseOK62

Exports:RoMLE.error

Dependencies: