R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
bayesEO
View on CRAN: Click
here
Download and install bayesEO package within the R console
Install from CRAN:
install.packages("bayesEO")
Install from Github:
library("remotes")
install_github("cran/bayesEO") Install by package version:
library("remotes")
install_version("bayesEO", "0.2.2") Attach the package and use:
library("bayesEO")
Maintained by
Gilberto Camara
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-06-04
Latest Update: 2024-06-04
Description:
ABayesian smoothing method for post-processing of remote sensing image classification which refines the labelling in a classified image in order to enhance its classification accuracy. Combines pixel-based classification methods with a spatial post-processing method to remove outliers and misclassified pixels.
How to cite:
Gilberto Camara (2024). bayesEO: Bayesian Smoothing of Remote Sensing Image Classification. R package version 0.2.2, https://cran.r-project.org/web/packages/bayesEO. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.2.1 (2024-06-04 11:44)
Other packages that cited bayesEO R package
View bayesEO citation profile
Other R packages that bayesEO depends,
imports, suggests or enhances
Complete documentation for bayesEO
Functions, R codes and Examples using
the bayesEO R package
Full bayesEO package
functions and examples
Downloads during the last 30 days
Today's Hot Picks in Authors and Packages
envirem
Generation of bioclimatic rasters that are complementary to the typical 19 bioclim variables. ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Pascal Title (view profile)
crossurr
Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebau ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Denis Agniel (view profile)
ibb
Call wrappers for Istanbul Metropolitan
Municipality's Open Data Portal (Turkish: Istanbul B ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Berk Orbay (view profile)
quickcode
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
msm
Functions for fitting continuous-time Markov and hidden
Markov multi-state models to longitudinal d ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Christopher Jackson (view profile)
27,268
R Packages
233,548
Dependencies
72,590
Author Associations
27,205
Publication Badges
