Package: btf
Type: Package
Title: Estimates univariate function via Bayesian trend filtering
Version: 1.0
Date: 2014-07-14
Author: Edward A. Roualdes
Maintainer: Edward A. Roualdes <edward.roualdes@uky.edu>
Description: 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.
License: GPL (>= 2.0)
Depends: R (>= 3.0.2)
Imports: Matrix, coda,
LinkingTo: Rcpp (>= 0.11.0), RcppEigen (>= 0.3.2.1.1)
NeedsCompilation: yes
Packaged: 2014-07-15 14:01:16 UTC; easy-e
Repository: CRAN
Date/Publication: 2014-07-15 16:42:44
