version 1.0

DESCRIPTION

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+Package: fastliu
+Title: Fast Functions for Liu Regression with Regularization Parameter
+        and Statistics
+Version: 1.0
+Date: 2024-02-02
+Authors@R: c(
+    person("Murat", "Genç", role = c("aut", "cre"), 
+    email="muratgenc@tarsus.edu.tr", comment=c(ORCID="0000-0002-6335-3044")),
+    person("Ömer", "Özbilen", role=c("aut"),
+      email="ozbilen@mersin.edu.tr"))
+Maintainer: Murat Genç <muratgenc@tarsus.edu.tr>
+Description: Efficient computation of the Liu regression coefficient paths, Liu-related statistics and 
+    information criteria for a grid of the regularization parameter. 
+    The computations are based on the 'C++' library 'Armadillo' through the 'R' package 'Rcpp'.
+License: GPL (>= 3)
+Encoding: UTF-8
+NeedsCompilation: yes
+RoxygenNote: 7.2.3
+LinkingTo: Rcpp, RcppArmadillo
+Imports: graphics, Rcpp, stats
+Depends: R (>= 3.6)
+Author: Murat Genç [aut, cre] (<https://orcid.org/0000-0002-6335-3044>),
+  Ömer Özbilen [aut]
+LazyData: true
+Packaged: 2024-02-04 19:11:27 UTC; murat
+Repository: CRAN
+Date/Publication: 2024-02-05 20:50:11 UTC

MD5

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+74b4b66df5c021b7884ef3b74a5fced7 *DESCRIPTION
+16dc7dea491fa838a3ecd77f68a9025b *NAMESPACE
+0ebab3f0f79867c62b46f83798d73c6b *R/RcppExports.R
+e49eae5899bbb66a4dbc0a19f47889e3 *R/coef-liureg.R
+efd38d9e466e11ffbfc1fbbf10eec094 *R/covliureg.R
+ecb219117f729a73e7e1121cbabc8440 *R/data.R
+81f06170c6ef4e0c777d350da245cacc *R/diagHliureg.R
+4b56832473d5183c20980cc28ebf8a3d *R/fastliu-package.R
+aff7a0388da839f4093eb7ba172c7cd2 *R/fastliu.R
+2c50ac796288f3253b3f2401ce860f59 *R/hatliureg.R
+5c14818d3af8c0c9b209dd6098601a5d *R/infoliu.R
+68c0db312d6e2c335667bbb9ae27ee2b *R/lamest.R
+5539ddc99ef39d021ecf50759d0f579c *R/plotfuns-liureg.R
+60f0e0f162c53ec6f28fcbaa1d890317 *R/predict-liureg.R
+ae698fa20e716fa52e3a579bcd31718a *R/pressliu.R
+aad43c6780353d16e29d5a4169290877 *R/print-liureg.R
+7de47ec59dba5de475221258fa1ad53d *R/print-statliu.R
+a56906452efe8b49c6cb9f411adc9efe *R/residuals-liureg.R
+0841043bc196384d0f9cf7edf7b83304 *R/statliu.R
+f8c24a9a67a58bf72802c9a4673ae7b9 *R/summary-liureg.R
+f01682ffd9d5582c0d3b8a226f3c2b16 *build/partial.rdb
+a6cecb1c44d71f78bd8a525fe3ff7cd4 *data/Hitters.rda
+3364e51c4655d7fb57e47f9f6e577334 *man/Hitters.Rd
+a1efb2f1d61dd7f1191431c867517b39 *man/coef.liureg.Rd
+8c591280df6cafc48c4ec3472124659f *man/covliu.Rd
+0798f4ca3333981802554054bda1a923 *man/diagHliu.Rd
+4f47ef51d0550a2a3f4d41986a589c0b *man/fastliu-package.Rd
+86f96a3e81816b40d6ed07e88783703d *man/hatliu.Rd
+74c124e4cc7ee49cc48c1dc14aad0740 *man/infoliu.Rd
+f4034546352d36584e3709a7045995e8 *man/lamest.Rd
+ff7a5716b4f733e7c71821ae040fea9b *man/liureg.Rd
+425eae5a79541a7ccc0f5a0b896023a1 *man/plot.liureg.Rd
+32d2b20782bffbea9a345e947b86e1f7 *man/predict.liureg.Rd
+bff94aad5c2d79113a2dae9a9633b751 *man/pressliu.Rd
+7916e7dad03055bea679d94dfdac89e3 *man/print.liureg.Rd
+1b800cd9ab154d5684721d9649c55216 *man/print.statliu.Rd
+99a2a84c34aeb5a0416f3ac8b0cc74c6 *man/residuals.liureg.Rd
+bb94c30340bd4c64ad5251d155d9f187 *man/statliu.Rd
+496cffb364d906cc1fc0f2b2498a22e4 *man/summary.liureg.Rd
+c89d6b95d18721894ab45341d0fbc7a6 *src/Makevars
+c89d6b95d18721894ab45341d0fbc7a6 *src/Makevars.win
+ba40cae73db8da4a6089b52044f83d0f *src/RcppExports.cpp
+2777869b0bfd8419fecd3b0327cccdd1 *src/coefliureg.cpp
+7b5e08051b70239e4baf68b24664a88e *src/coefliureg.h
+c6c8b1fdbfda87be9c81c6643af5c62a *src/covliu.cpp
+c2f91aa07e2f98b5958aacb58cf3a193 *src/diagH.cpp
+7961987c40c57e2da075573916aa27a8 *src/hat.cpp
+3fc003086ad9c922d7003abf52188116 *src/liuoptlam.cpp
+0a66f18be79432898c61607e8fa5269f *src/liureg.cpp
+ca6869893dffc71ec7f2941764b0e104 *src/liureg.h
+4cf9f9d39f1a774dff24e98120ba2401 *src/liustats.cpp
+a71c19610d77966ed9dbc27a37ef8d82 *src/predictliureg.cpp
+0c21a96c6d5e34a94abc6b4e019b5374 *src/predictliureg.h
+f1fb25fdf3c00efd9ac0e22becfd5723 *src/press.cpp
+58158f23e13ef7cd9ddfd2d0568d15e3 *src/samp.cpp
+b75b15d7319ac1e7df5336866bea5132 *src/samp.h

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+S3method(coef,liureg)
+S3method(plot,liureg)
+S3method(predict,liureg)
+S3method(print,liureg)
+S3method(print,statliu)
+S3method(residuals,liureg)
+S3method(summary,liureg)
+export(covliu)
+export(diagHliu)
+export(hatliu)
+export(infoliu)
+export(lamest)
+export(liureg)
+export(pressliu)
+export(statliu)
+importFrom(Rcpp,sourceCpp)
+importFrom(graphics,legend)
+importFrom(graphics,matplot)
+importFrom(graphics,mtext)
+importFrom(graphics,text)
+importFrom(stats,coef)
+importFrom(stats,pnorm)
+importFrom(stats,symnum)
+importFrom(stats,var)
+useDynLib(fastliu, .registration = TRUE)

R/RcppExports.R

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+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+coef_liureg <- function(obj) {
+    .Call(`_fastliu_coef_liureg`, obj)
+}
+
+covliucpp <- function(obj) {
+    .Call(`_fastliu_covliucpp`, obj)
+}
+
+diagHcpp <- function(obj) {
+    .Call(`_fastliu_diagHcpp`, obj)
+}
+
+hatcpp <- function(obj) {
+    .Call(`_fastliu_hatcpp`, obj)
+}
+
+liuoptlamcpp <- function(obj) {
+    .Call(`_fastliu_liuoptlamcpp`, obj)
+}
+
+liuregcpp <- function(Xmat, yvec, lambda, scale) {
+    .Call(`_fastliu_liuregcpp`, Xmat, yvec, lambda, scale)
+}
+
+liustatscpp <- function(obj) {
+    .Call(`_fastliu_liustatscpp`, obj)
+}
+
+predict_liureg <- function(obj, newdata) {
+    .Call(`_fastliu_predict_liureg`, obj, newdata)
+}
+
+pressliucpp <- function(obj) {
+    .Call(`_fastliu_pressliucpp`, obj)
+}
+

R/coef-liureg.R

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+#' Extract coefficient estimates from a liureg object
+#'
+#' Prints coefficient estimates from a
+#' fitted \code{liureg} object.
+#'
+#' @param object A \code{liureg} object.
+#' @param ... Not used in this implementation.
+#'
+#' @method coef liureg
+#'
+#' @return The returned object is a data.frame containing the coefficients path.
+#' @author Murat Genç
+#' @export
+#'
+#' @seealso [liureg()], [predict()], [summary()], [pressliu()], [residuals()]
+#' @examples
+#' data("Hitters")
+#' Hitters <- na.omit(Hitters)
+#' X <- model.matrix(Salary ~ ., Hitters)[, -1]
+#' y <- Hitters$Salary
+#' lam <- seq(0, 1, 0.01)
+#' liu.mod <- liureg(X, y, lam)
+#' coef(liu.mod)
+coef.liureg <- function(object, ...){
+  betaorj <- coef_liureg(object)
+  rownames(betaorj) <- c("Intercept", object$cnames)
+  colnames(betaorj) <- object$lnames
+  betaorj
+}

R/covliureg.R

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+#' Covariance matrix based on a fitted liureg object.
+#'
+#' For a scalar or vector tuning parameter lambda,
+#'    the \code{covliureg} computes the covariance matrix
+#'    for the estimates of a Liu regression model.
+#'
+#' @param obj A \code{liureg} object.
+#' @return The returned object is a list of the matrix of estimated covariances.
+#' @author Murat Genç and Ömer Özbilen
+#' @export
+#'
+#' @seealso [liureg()], [coef()], [predict()], [summary()], [pressliu()], [residuals()]
+#' @examples
+#' data("Hitters")
+#' Hitters <- na.omit(Hitters)
+#' X <- model.matrix(Salary ~ ., Hitters)[, -1]
+#' y <- Hitters$Salary
+#' lam <- seq(0, 1, 0.01)
+#' liu.mod <- liureg(X, y, lam)
+#' # List of covariance matrices for 101 lambda values
+#' cov.mat <- covliu(liu.mod)
+#' print(cov.mat$lam1)
+covliu <- function(obj){
+  covliu <- covliucpp(obj)
+  names(covliu) <- obj$lnames
+  for(i in 1:length(covliu)){
+    rownames(covliu[[i]]) <- colnames(covliu[[i]]) <- obj$cnames
+  }
+  covliu
+}
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R/data.R

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+#' Hitters
+#'
+#' Major League Baseball Data from the 1986 and 1987 seasons.
+#'
+#' @name Hitters
+#' @format A data frame with 322 observations of major league players
+#' on the following 20 variables with explanations.
+#' \tabular{lll}{
+#'   \code{AtBat} \tab \tab Number of times at bat in 1986\cr
+#'   \tab \cr
+#'   \code{Hits} \tab \tab Number of hits in 1986\cr
+#'   \tab \cr
+#'   \code{HmRun} \tab \tab Number of home runs in 1986\cr
+#'   \tab \cr
+#'   \code{Runs} \tab \tab Number of runs in 1986\cr
+#'   \tab \cr
+#'   \code{RBI} \tab \tab Number of runs batted in 1986\cr
+#'   \tab \cr
+#'   \code{Walks} \tab \tab Number of walks in 1986\cr
+#'   \tab \cr
+#'   \code{Years} \tab \tab Number of years in the major leagues\cr
+#'   \tab \cr
+#'   \code{CAtBat} \tab \tab Number of times at bat during his career\cr
+#'   \tab \cr
+#'   \code{CHits} \tab \tab Number of hits during his career\cr
+#'   \tab \cr
+#'   \code{CHmRun} \tab \tab Number of home runs during his career\cr
+#'   \tab \cr
+#'   \code{CRuns} \tab \tab Number of runs during his career\cr
+#'   \tab \cr
+#'   \code{CRBI} \tab \tab Number of runs batted in during his career\cr
+#'   \tab \cr
+#'   \code{CWalks} \tab \tab Number of walks during his career\cr
+#'   \tab \cr
+#'   \code{League} \tab \tab A factor with levels A and N indicating player's league at the end of 1986\cr
+#'   \tab \cr
+#'   \code{Division} \tab \tab A factor with levels E and W indicating player's division at the end of 1986\cr
+#'   \tab \cr
+#'   \code{PutOuts} \tab \tab Number of put outs in 1986\cr
+#'   \tab \cr
+#'   \code{Assists} \tab \tab Number of assists in 1986\cr
+#'   \tab \cr
+#'   \code{Errors} \tab \tab Number of errors in 1986\cr
+#'   \tab \cr
+#'   \code{Salary} \tab \tab 1987 annual salary on opening day in thousands of dollars\cr
+#'   \tab \cr
+#'   \code{NewLeague} \tab \tab A factor with levels A and N indicating player's league at the beginning of 1987\cr
+#'   \tab \cr
+#' }
+#' @source The dataset was retrieved from the StatLib library maintained at
+#' Carnegie Mellon University. This is part of the data used in the 1988
+#' ASA Graphics Section Poster Session. The dataset is available in the R package
+#' ISLR2 (James et al., 2022). For more details, see the book,
+#' *An Introduction to Statistical Learning with applications in R*
+#' by James et al. (2013).
+#' @references James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013).
+#' An Introduction to Statistical Learning with applications in R,
+#' \url{https://www.statlearning.com}, *Springer-Verlag*, New York.
+#'
+#' James G, Witten D, Hastie T, Tibshirani R (2022). *ISLR2: Introduction to Statistical Learning, Second Edition*.
+#' R package version 1.3-2, \url{https://CRAN.R-project.org/package=ISLR2}.
+NULL

R/diagHliureg.R

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+#' Diagonal Elements of the Hat Matrix
+#'
+#' For each value of the regularization parameter lambda,
+#'    \code{diagHliu} returns the diagonal elements of the hat matrix.
+#'    Unlike the \code{hatliu} function, only the diagonal
+#'    elements of the hat matrix are calculated, thus the
+#'    computation of diagonal elements is faster than \code{hatliu}.
+#'
+#' @param obj A \code{liureg} object
+#'
+#' @return The returned object is a matrix whose columns are the
+#'    diagonal elements of the hat matrix for each value of the
+#'    lambda regularization parameter.
+#' @author Murat Genç
+#' @export
+#'
+#' @seealso [liureg()], [summary()], [pressliu()], [residuals()]
+#'
+#' @examples
+#' data("Hitters")
+#' Hitters <- na.omit(Hitters)
+#' X <- model.matrix(Salary ~ ., Hitters)[, -1]
+#' y <- Hitters$Salary
+#' lam <- seq(0, 1, 0.01)
+#' liu.mod <- liureg(X, y, lam)
+#' diagHliu(liu.mod)
+diagHliu <- function(obj){
+  diagH <- diagHcpp(obj)
+  rownames(diagH) <- obj$rnames
+  colnames(diagH) <- obj$lnames
+  diagH
+}
+
+
+

R/fastliu-package.R

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+#' @keywords internal
+"_PACKAGE"
+
+## usethis namespace: start
+#' @importFrom Rcpp sourceCpp
+#' @importFrom graphics legend
+#' @importFrom graphics matplot
+#' @importFrom graphics mtext
+#' @importFrom graphics text
+#' @importFrom stats coef
+#' @importFrom stats pnorm
+#' @importFrom stats symnum
+#' @importFrom stats var
+#' @useDynLib fastliu, .registration = TRUE
+## usethis namespace: end
+NULL