Depends: R (>= 3.5.0), mvtnorm, ggplot2, survival,

Depends: R (>= 2.10), mvtnorm, ggplot2, survival,
Packaged: 2019-12-16 19:33:41 UTC; hhelferhoeltgebaum

Title: High Dimensional Bayesian Ridge Regression without MCMC
Authors@R: c(person("Sergio Perez-Elizalde", "Developer", role = "aut"),
person("Blanca Monroy-Castillo", "Developer", role = c("aut","cre"),
person("Paulino Perez-Rodriguez", "User", role = "ctb"))
Description: The svd(singular value decomposition) or qr decomposition was using for the implementation, this avoid the recursion optimizing the time in the compute
Imports: numDeriv, parallel, bigstatsr, MASS
Author: Sergio Perez-Elizalde Developer [aut],
Blanca Monroy-Castillo Developer [aut, cre],
Maintainer: Blanca Monroy-Castillo Developer <blancamonroy.96@gmail.com>

Description: The svd(singular value decomposition) or qr decomposition was using for the implementation, this avoid the recursion optimizing the time in the compute.
Imports: numDeriv, parallel, bigstatsr, MASS, graphics

person("Paulino Perez-Rodriguez", "User", role = "ctb"),
person("Jose Crossa", "User", role = "ctb"))

Description: Ridge regression provide biased estimators of the regression parameters with lower variance. The HDBRR ("High Dimensional Bayesian Ridge Regression") function fits Bayesian Ridge regression without MCMC, this one uses the SVD or QR decomposition for the posterior computation.

Title: High Dimensional Confidence Interval Based on Lasso and
Author: Hanzhong Liu, Xin Xu, Jingyi Jessica Li
Imports: glmnet, slam, parallel, foreach, iterators, doParallel,
Description: Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.

Title: Hierarchical Derivative Curve Estimation
person(given = "Garritt", family = "L. Page", email = "page@stat.byu.edu", role = c("aut", "cre")),
person(given = "Maria Xose", family = "Rodriguez-Alvarez", email = "mxrodriguez@bcamath.org", role = c("aut")),
person(given = "Dae-Jin", family = "Lee", email = "dlee@bcamath.org", role = c("ctb")),
person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("ctb")),
person(given = "Radford M. Neal", family = "Neal", role = c("ctb")))
Description: A procedure that fits derivative curves based on a sequence of quotient differences.  In a hierarchical setting the package produces estimates of subject-specific and group-specific derivative curves.  In a non-hierarchical setting the package produces a single derivative curve.
Maintainer: Garritt L. Page <page@stat.byu.edu>