README.md

In hrmJ/phdBayes: Shortcuts For The Bayesian Analyses In My PhD

Help installing on Ubuntu

Packages to install:

sudo apt-get install jags

Usage

Creating a model

library(phdBayes)
model = StandardBayesian(d, "testmodel", c('subjtype','corpustype'))
SaveOriginalData(model)
CreateAndRunModel(model, list("n.chains" = 2, "sample"=70000, "adapt" = 10000, "burnin" = 9000, "thin" = 1, "method" = "parallel"))
model@datalist = LoadResults(model)
PrintSvg(model)

Extracting data from a saved model

Getting all the data

library(phdBayes)
model = StandardBayesian(yamlpath="/root/", dumppath="/root/")
model@datalist = LoadResults(model,lang="fi")

Here's an example script for using on a remote server:

library(stats)                                                                                            
library(methods)
library(phdBayes)                                                                                         
model = StandardBayesian(yamlpath="./",dumppath="./")                                                                
model@datalist = LoadResults(model,lang="fi")                                                             
saveRDS(model@datalist, "path/to/datalist.rds") 

Extracting plots to pdfs or svgs

The plots produced by ggmcmc require a huge amount of memory, so it is probably a good idea to just use pdfs or svgs instead of actual ggplot objects.

For this purpose, the function SavePdf can be used, e.g.:

general <- ReadData("general_new")
SavePdf(general,"std.all",2,5)
SavePdf(general,"std.interact")
SavePdf(general,"general_new", "funct")

hrmJ/phdBayes documentation built on May 25, 2019, 7:21 p.m.