btf: Estimates Univariate Function via Bayesian Trend Filtering

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 sub-Gaussian 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

AuthorEdward A. Roualdes
MaintainerEdward A. Roualdes <[email protected]>
LicenseGPL (>= 2.0)
Package repositoryView on CRAN
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btf documentation built on May 31, 2017, 8:22 p.m.