I am currently trying to interpolate quarterly accounting data into weekly data. Even though I know the significance of these could become quite weak I need to do it to some data points.
Currently I am reading a lot about a package called tempdisagg, which follows a denton-cholette approach to this, but other people suggest to do it through the approx function in R. Even though, I would like to ask for your opinion on how to approach this problem the best way.
After reviewing the paper on tempdisagge, I think you should take advantage of it. The denton-cholette algorithm is only one of available methods, with chow-lin-maxlog as the default.
Without a reproducible example, called a reprex and a notion of the domain, it's hard to give specific advice on how best to tune the methods in the package to your situation. However, a time series specific approach is more likely to give you better results than simple approaches, such as approxfun{stats} based on simple linear approximation.