[Rcpp-devel] Input on code design implementing a MCMC algorithm in R and improving performance with RcppArmadillo

Hi Dirk,
Below is my question in text format since there were troubles with the
html formating.

I want to „translate“ a MCMC algorithm written in matlab to R to
eventually release it in a package. In the matlab version model input,
state of the chain and chain output is stored in structs. Updating
different parameters of the underlying model is performed with
different functions. I already have a very raw R version where these
structs are implemented as S4 classes and updates are performed with
generic functions taking both classes as input. I would like to
increase performance with RcppArmadillo. However, I struggle to choose
a good approach since I am not very experienced in any of the above
subjects and have difficulties putting together the different concepts.
It would be very helpful if you could give me your thoughts on what I
think my main options are, tell me in case I misunderstood some
concepts or point me into a better direction.
 
Option 1: mainly R
Keeping R S4 classes (or rewrite them as Reference Classes since I
think they would have been a better choice for defining a class storing
states of a model) and the algorithm written in R and write updating
functions in RcppArmadillo. These functions can be exposed to R with
Rcpp modules or attributes.
+ possibly the easiest version since I only have to rewrite the
functions in Rcpp
- Still a lot of R which could come with performance costs
 
Option2: mainly Rcpp
Define one Cpp class which stores input and updated parameters as
member variables and the updating functions as member functions. Then I
could write the main MCMC algorithm as a separate function that creates
an instance of this class, calls the updating functions and returns a
list containing the output. I could only expose this main algorithm
(with Rcpp modules or attributes) to R and avoid exposing the internal
classes. (Currently I don’t think exposure of the classes is necessary
and seems more difficult than exposing functions).The part involving
the class is taken from the Kalman filter example (RcppArmadillo-intro
vignette) and I imagine the structure of the algorithm function and
returned list similar to the gallery entry on the EM Algorithm for
Probit Regressions
(https://gallery.rcpp.org/articles/EM-algorithm-example/#attempt-1[https://deref-gmx.net/mail/client/Q6JdcN6Rp84/dereferrer/?redirectUrl=https%3A%2F%2Fgallery.rcpp.org%2Farticles%2FEM-algorithm-example%2F%23attempt-1[https://deref-gmx.net/mail/client/Q6JdcN6Rp84/dereferrer/?redirectUrl=https%3A%2F%2Fgallery.rcpp.org%2Farticles%2FEM-algorithm-example%2F%23attempt-1]]).
+ probably faster
+ possibly cleaner
- more difficult and I have very little Cpp experience (especially with
classes)
 
Personally, I aim for a compromise between performance, implementation
difficulty and the best approach since this is for my master’s thesis
and I also have to consider the deadline. I think this compromise would
be to stay with the main R version but rewrite the S4 classes as
Reference Class.
I'm looking forward to hearing your feedback, thoughts and experiences,
Eva

 

Gesendet: Donnerstag, 09. April 2020 um 14:51 Uhr
Von: "Dirk Eddelbuettel" <edd at debian.org>
An: "eva lehner" <eva-valerie at gmx.at>
Cc: rcpp-devel at lists.r-forge.r-project.org
Betreff: Re: [Rcpp-devel] Input on code design implementing a MCMC
algorithm in R and improving performance with RcppArmadillo
Hi Eva,

My email client doesn't display you html email, possibly a fault at my
end.
But text-only email is still a default in most places. Can you maybe
resend
text-only please? Thanks!

Cheers, Dirk

--
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