Performs multivariate nonparametric regression/classification by the method of sieves (using orthogonal basis). The method is suitable for moderate highdimensional features (dimension < 100). The l1penalized sieve estimator, a nonparametric generalization of Lasso, is adaptive to the feature dimension with provable theoretical guarantees. We also include a nonparametric stochastic gradient descent estimator, SieveSGD, for online or large scale batch problems. Details of the methods and model assumptions can be found in: <arXiv:2206.02994> <arXiv:2104.00846>.
Package details 


Author  Tianyu Zhang 
Maintainer  Tianyu Zhang <tianyuz3@andrew.cmu.edu> 
License  GPL2 
Version  2.0 
Package repository  View on CRAN 
Installation 
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