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Trend filtering uses the generalized lasso framework to fit an adaptive polynomial of degree k to estimate the function f_0 at each input x_i in the model: y_i = f_0(x_i) + epsilon_i, for i = 1, ..., n, and epsilon_i is subGaussian with E(epsilon_i) = 0. Bayesian trend filtering adapts the genlasso framework to a fully Bayesian hierarchical model, estimating the penalty parameter lambda within a tractable Gibbs sampler.
Package details 


Author  Edward A. Roualdes 
Maintainer  Edward A. Roualdes <[email protected]> 
License  GPL (>= 2.0) 
Version  1.2 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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