8 citations · 10 across the 12 of their papers we have counts for
4 papers · 1 filter
Change-point regression with a smooth additive disturbance
Florian Pein, Rajen D. Shah
We assume a nonparametric regression model where the signal is given by the sum of a piecewise constant function and a smooth function. To detect the change-points and estimate the…
Cross-validation for change-point regression: pitfalls and solutions
Florian Pein, Rajen D. Shah
Cross-validation is the standard approach for tuning parameter selection in many non-parametric regression problems. However its use is less common in change-point regression, perh…
High-dimensional regression with potential prior information on variable importance
Benjamin G. Stokell, Rajen D. Shah
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…
Structure Learning for Directed Trees
Martin Emil Jakobsen, Rajen D. Shah, Peter Bühlmann +1
Knowing the causal structure of a system is of fundamental interest in many areas of science and can aid the design of prediction algorithms that work well under manipulations to t…