From ada38fb88810de899fcd98dd5ee67a88cf535789 Mon Sep 17 00:00:00 2001 From: jaredhuling Date: Sat, 27 Jul 2024 11:43:51 -0500 Subject: [PATCH] manual update --- R/oem.R | 2 +- man/oem.Rd | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/R/oem.R b/R/oem.R index 11a3c7c..448df2f 100644 --- a/R/oem.R +++ b/R/oem.R @@ -73,7 +73,7 @@ #' faster in certain situations, ie when n >> p #' @return An object with S3 class "oem" #' @references Shifeng Xiong, Bin Dai, Jared Huling, and Peter Z. G. Qian. Orthogonalizing -#' EM: A design-based least squares algorithm. Technometrics, 58(3):285-293, 2016. \url{https://doi.org/10.1080/00401706.2015.1054436} +#' EM: A design-based least squares algorithm. Technometrics, 58(3):285-293, 2016. \doi{10.1080/00401706.2015.1054436} #' @useDynLib oem, .registration=TRUE #' @import Rcpp #' @import Matrix diff --git a/man/oem.Rd b/man/oem.Rd index 27a85b8..b9e1353 100644 --- a/man/oem.Rd +++ b/man/oem.Rd @@ -215,7 +215,7 @@ max(abs(res.gr$beta[[1]] - res.gr.s$beta[[1]])) } \references{ Shifeng Xiong, Bin Dai, Jared Huling, and Peter Z. G. Qian. Orthogonalizing -EM: A design-based least squares algorithm. Technometrics, 58(3):285-293, 2016. \url{https://amstat.tandfonline.com/doi/abs/10.1080/00401706.2015.1054436} +EM: A design-based least squares algorithm. Technometrics, 58(3):285-293, 2016. \doi{10.1080/00401706.2015.1054436} Huling. J.D. and Chien, P. (2022), Fast Penalized Regression and Cross Validation for Tall Data with the oem Package. Journal of Statistical Software 104(6), 1-24. doi:10.18637/jss.v104.i06