jagsUI v.1.5.2

Remove View function due to problematic interactions with RStudio
Improvements to traceplot and densityplot
Make sure output is reproducible when parallel=FALSE
Minor bugfixes

jagsUI v1.5.1

Fix issue when chains adapted for different numbers of iterations
Fix crash when DIC was requested but JAGS couldn't calculate it
Stop auto-converting 1 row/1 col matrices into vectors
Improve pp.check plotting function (thanks to Mike Meredith)
Add some warnings about functions and arguments that will be deprecated soon

jagsUI v1.4.4

What's new in v1.4.4:

1. Bugfix to allow running chains in parallel when dependencies are in non-standard libraries.
2. Changed default approach to generating random seeds.
3. Add S3 method for View() and convert traceplot() to an S3 method from S4 (thanks to Mike Meredith).

This version is now on CRAN as well.

---

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).
2. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download jagsUI_1.4.4.zip.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download jagsUI_1.4.4.tar.gz.

Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.4.2

What's new in v1.4.2:

1. Fix dependency issues and update namespace to meet new package building standards.
2. Add ability to manually specify the number of CPU cores to use when running in parallel.
3. Various output processing bugfixes.

This version is now on CRAN as well.

---

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).
2. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.4.2.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.4.2.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3.7

What's new in v1.3.7:

1. Fix problem with max.iter argument in autojags(). Clarify documentation and output for autojags().
2. Change method for closing connection to clusters when running in parallel to avoid closing unrelated connections. Adjust output for jags.basic.
3. Add verbose argument to functions to allow suppression of all text output in the console as the function runs.

This version is live on CRAN.

---

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).

2. Run the following code in R (optional, but highly recommended to make sure you have the latest versions of the dependencies):

    remove.packages(c('coda','rjags'))
    install.packages(c('coda','rjags'))
   

3. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.3.7.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.3.7.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3.4

What's new in v1.3.4:

Added option save.all.iter in autojags() function to combine MCMC samples from all iterative updates into final posterior.

---

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).

2. Run the following code in R (optional, but highly recommended to make sure you have the latest versions of the dependencies):

    remove.packages(c('coda','rjags'))
    install.packages(c('coda','rjags'))
   

3. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.3.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.3.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3.3

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).

2. Run the following code in R (optional, but highly recommended to make sure you have the latest versions of the dependencies):

    remove.packages(c('coda','rjags'))
    install.packages(c('coda','rjags'))
   

3. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.3.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.3.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3.2

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).

2. Run the following code in R (optional, but highly recommended to make sure you have the latest versions of the dependencies):

    remove.packages(c('coda','rjags'))
    install.packages(c('coda','rjags'))
   

3. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.3.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.3.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3.1

This package provides a set of wrappers around rjags functions to run Bayesian analyses in JAGS (specifically, via libjags). A single function call can control adaptive, burn-in, and sampling MCMC phases, with MCMC chains run in sequence or in parallel. Posterior distributions are automatically summarized (with the ability to exclude some monitored nodes if desired) and functions are available to generate figures based on the posteriors (e.g., predictive check plots, traceplots). Function inputs, argument syntax, and output format are nearly identical to the R2WinBUGS/R2OpenBUGS packages to allow easy switching between MCMC samplers.

Install Instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).

2. Run the following code in R (optional, but highly recommended to make sure you have the latest versions of the dependencies):

    remove.packages(c('coda','rjags'))
    install.packages(c('coda','rjags'))
   

3. Choose package installation method from the options below.

To install directly from CRAN:

install.packages('jagsUI')

Manual Windows install instructions:

Download "jagsUI_1.3.zip" file.
From the R menu, select "Packages >> Install package(s) from local zip files"
Navigate to the downloaded .zip file and select.

Manual Mac / Linux install instructions (from source):

Download "jagsUI_1.3.tar.gz" file.
Run the following code in R:

install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms):

install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")

jagsUI v1.3

Windows install instructions:

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/).

2. Download "jagsUI_1.3.zip" file.

3. Install, or remove and re-install, the coda and rjags packages:

   remove.packages(c('coda','rjags'))
   install.packages(c('coda','rjags'))
   

4. From the R menu, select "Packages >> Install package(s) from local zip files"

5. Navigate to the downloaded .zip file and select.

Mac / Linux install instructions (from source):

1. Install the latest version of JAGS on your computer (http://sourceforge.net/projects/mcmc-jags/files/JAGS/). If you have a 64-bit OS, you may need to install both the 32 and 64 bit versions of JAGS (if available).
2. Download "jagsUI_1.3.tar.gz" file.
3. Run the following code in R (first two lines are optional, but highly recommended if you have coda and rjags installed already):

remove.packages(c('coda','rjags'))
install.packages(c('coda','rjags'))
install.packages("PATH/TO/TAR.GZ", repos = NULL, type="source")

Alternative install instructions (all platforms, again first line is optional):

remove.packages(c('coda','rjags'))
install.packages("devtools")
library(devtools)
install_github("kenkellner/jagsUI")