High-dimensional regression with potential prior information on variable importance. (arXiv:2109.11281v2 [stat.ME] UPDATED)

There are a variety of settings where vague prior information may be
available on the importance of predictors in high-dimensional regression
settings. Examples include ordering on the variables offered by their empirical
variances (which is typically discarded through standardisation), the lag of
predictors when fitting autoregressive models in time series settings, or the
level of missingness of the variables. Whilst such orderings may not match the
true importance of variables, we argue that there is little to be lost, and …

arxiv importance information prior regression