SCM

R Development Page

Contributed R Packages

Below is a list of all packages provided by project dcr - Data Cloning in R.

Important note for package binaries: R-Forge provides these binaries only for the most recent version of R, but not for older versions. In order to successfully install the packages provided on R-Forge, you have to switch to the most recent version of R or, alternatively, install from the package sources (.tar.gz).

Packages

PVAClone

Population Viability Analysis with Data Cloning

  Likelihood based population viability analysis in the presence of observation error and missing data. The package can be used to fit, compare, predict, and forecast various growth model types using data cloning.
  Version: 0.1-2 | Last change: 2014-05-19 10:35:51+02 | Rev.: 1063
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get PVAClone 0.1-6 from CRAN
  R install command: install.packages("PVAClone", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


ResourceSelection

Resource Selection (Probability) Functions for Use-Availability Data

  Resource Selection (Probability) Functions for use-availability wildlife data as described in Lele and Keim (2006, Ecology 87, 3021--3028), and Lele (2009, J. Wildlife Management 73, 122--127).
  Version: 0.2-4 | Last change: 2014-05-19 10:35:51+02 | Rev.: 1063
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get ResourceSelection 0.3-5 from CRAN
  R install command: install.packages("ResourceSelection", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


dclone

Data Cloning and MCMC Tools for Maximum Likelihood Methods

  Low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte Carlo methods. Sequential and parallel MCMC support for JAGS, WinBUGS and OpenBUGS.
  Version: 2.0-0 | Last change: 2013-10-01 21:05:32+02 | Rev.: 1045
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get dclone 2.3-0 from CRAN
  R install command: install.packages("dclone", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


dcmle

Hierarchical Models Made Easy with Data Cloning

  S4 classes around infrastructure provided by the dclone package to make package development with data cloning for hierarchical models easy as a breeze.
  Version: 0.2-4 | Last change: 2013-10-01 21:06:12+02 | Rev.: 1046
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get dcmle 0.3-1 from CRAN
  R install command: install.packages("dcmle", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


detect

Analyzing Wildlife Data with Detection Error

  The package implements models to analyze site occupancy and count data models with detection error. The package development was supported by the Alberta Biodiversity Monitoring Institute (ABMI) and the Boreal Avian Modelling (BAM) Project.
  Version: 0.3-2 | Last change: 2014-05-16 18:57:03+02 | Rev.: 1062
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get detect 0.4-2 from CRAN
  R install command: install.packages("detect", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


pbapply

Adding Progress Bar to *apply Functions

  A lightweight package that adds progress bar to vectorized R functions (*apply). The implementation can easily be added to functions, where showing the progress is useful for the user (e.g. bootstrap).
  Version: 1.1-1 | Last change: 2014-05-16 18:32:46+02 | Rev.: 1061
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get pbapply 1.4-2 from CRAN
  R install command: install.packages("pbapply", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)


sharx

Models and Data Sets for the Study of Species-Area Relationships

  Data sets and SAR, SARX, HSAR and HSARX models as described in Solymos and Lele (2012, GEB 21, 109-120).
  Version: 1.0-4 | Last change: 2014-05-19 10:35:51+02 | Rev.: 1063
  Download: linux(.tar.gz) | windows(.zip) | Build status: Current | Stable Release: Get sharx 1.0-5 from CRAN
  R install command: install.packages("sharx", repos="http://R-Forge.R-project.org")
 
Logs:  
Package build: Source package (Linux x86_64) Windows binary (x86_64/i386)
Package check: Linux x86_64 (patched) | Linux x86_64 (devel) Windows (patched) | Windows (devel)

 

Build status codes

0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
5 - Offline: the package is not available. The build system may be offline or the package maintainer did not trigger a rebuild (done e.g., via committing to the package repository).

If your package is not shown on this page or not building, then check the build system status report.

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