Type: Package
Package: btf
Title: Estimates Univariate Function via Bayesian Trend Filtering
Version: 1.2
Date: 2017-05-30
Author: Edward A. Roualdes
Maintainer: Edward A. Roualdes <eroualdes@csuchico.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 (>= 3.1.0)
Imports: Rcpp (>= 0.12.0), Matrix, coda,
LinkingTo: Rcpp (>= 0.12.0), RcppEigen (>= 0.3.2.2.0)
VignetteBuilder: knitr
Suggests: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-05-30 17:49:04 UTC; ez
Repository: CRAN
Date/Publication: 2017-05-31 06:22:42 UTC
