Latest version of nimble (1.2.0) generates the following error message when executing the expfit() function:

library(baorista)
data(samplemat) 
x.mat <- createProbMat(pmat=samplemat,timeRange=c(5000,3001),resolution=100)
exponential.fit <- expfit(x.mat) #fitting using default MCMC/Prior settings

Compiling nimble model...
Error in FUN(X[[i]], ...) :
checkAndPrepareDistributionInfo: random generation function rAExp is missing returnType or returnType does not match the type of the x argument to the corresponding density function.

The problem is most likely caused by inconsistencies between the random number generator function and the custom probability distribution.
Downgrading nimble to 1.1.0 fixes the problem (e.g. running devtools::install_version('nimble',version='1.1.0')) , but an update of expfit(), logisticfit() and icarfit() is required, or alternatively the issue is with nimble 1.2.0 itself. nimble developers have been contacted for help.

• Add error message in case users provide unsupported probability distribution as prior.
• Fix BUG on expfit() where rPrior argument is not correctly implemented in the model definition. (Possibly release earlier on version 0.1.5?)
• UPDATE all models so that inits values are derived explicitly from random draws of the prior.
• add NEW model based on double exponential growth

• Please always explain all acronyms in the description text. -> ICAR

The Description field is intended to be a (one paragraph) description of what the package does and why it may be useful. Please add more details about the package functionality and implemented methods in your Description text.

• Please add \value to .Rd files regarding exported methods and explain the functions results in the documentation. Please write about the structure of the output (class) and also what the output means. (If a function does not return a value, please document that too, e.g. \value{No return value, called for side effects} or similar) -> Missing Rd-tags:

  plot.fittedExp.Rd: \value
  plot.fittedICAR.Rd: \value
  plot.fittedLogistic.Rd: \value
  plot.probMat.Rd: \value

• \dontrun{} should only be used if the example really cannot be executed (e.g. because of missing additional software, missing API keys, ...) by the user. That's why wrapping examples in \dontrun{} adds the comment ("# Not run:") as a warning for the user. Does not seem necessary. Please replace \dontrun with \donttest.

Please unwrap the examples if they are executable in < 5 sec, or replace dontrun{} with \donttest{}.

• You write information messages to the console that cannot be easily suppressed.

It is more R like to generate objects that can be used to extract the information a user is interested in, and then print() that object. Instead of print()/cat() rather use message()/warning() or if(verbose)cat(..) (or maybe stop()) if you really have to write text to the console. (except for print, summary, interactive functions) -> R/expfit.R, R/icarfit.R, R/logisticfit.R

• Please make sure that you do not change the user's options, par or working directory. If you really have to do so within functions, please ensure with an immediate call of on.exit() that the settings are reset when the function is exited.

e.g.:
...
oldpar <- par(no.readonly = TRUE) # code line i
on.exit(par(oldpar)) # code line i + 1
...
par(mfrow=c(2,2)) # somewhere after
...
If you're not familiar with the function, please check ?on.exit. This function makes it possible to restore options before exiting a function even if the function breaks. Therefore it needs to be called immediately after the option change within a function.
-> R/plotfittedExp.R, R/plotfittedICAR.R , R/plotfittedLogistic.R

• Please do not modifiy the .GlobalEnv. This is not allowed by the CRAN policies. -> R/expfit.R, R/icarfit.R, R/logisticfit.R