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

c(person("Sergio Perez-Elizalde", "Developer", role = "aut"),
person("Blanca Monroy-Castillo", "Developer", role = c("aut","cre"),
email = "blancamonroy.96@gmail.com"),
person("Paulino Perez-Rodriguez", "User", role = "ctb"),
person("Jose Crossa", "User", role = "ctb"))
Sergio Perez-Elizalde Developer [aut],
Blanca Monroy-Castillo Developer [aut, cre],
Paulino Perez-Rodriguez User [ctb],
Jose Crossa User [ctb]

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.

High Dimensional Confidence Interval Based on Lasso and
Bootstrap
glmnet, slam, parallel, foreach, iterators, doParallel,
lattice, Matrix, mvtnorm
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.

c(
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")))
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.
Garritt L. Page [aut, cre],
Maria Xose Rodriguez-Alvarez [aut],
Dae-Jin Lee [ctb],
S. McKay Curtis [ctb],
Radford M. Neal Neal [ctb]