Ecological momentary assessment data are everywhere these days. In psychology, dynamic structural equation models (DSEMs) are particularly attractive for analyzing such data. In this paper Ethan McCormick and I show how you can easily incorporate nonlinear trends and cycles using splines.

and then do some tiny changes that removed the issue and kept the package on CRAN. Morale of the story: CRAN rules are there for a reason, and it's possible to figure things out if you just try obsessively enough.
Now time for resubmission!

Oh joy! BDR found a subtle warning on Fedora with gcc15 with very strict compiler flags that threatened to kick my galamm #rstats pkg out of CRAN by Saturday. After a week of headscratching I managed to set up my old Ubuntu laptop to reproduce the error :-)

so here we've instead developed nested sequential Monte Carlo algoriths, SMC^2 among friends. We derive the algorithms for a very general case of the Mallows model, and test them on complete rankings, top-3 rankings, pairwise preferences, and clustering. An additional advantage of SMC^2 is that

Preprint! The Bayesian Mallows model is a very flexible model for analyzing rank and preference data, and has been applied across a large number of domains. In many cases, however, the data naturally arrive sequentially in time. Existing Metropolis-Hastings algorithms scale poorly in this case