From b447763b394eb653ba967604c1bbcf083b201c44 Mon Sep 17 00:00:00 2001 From: WANG Zhiwei <48282751+statwangz@users.noreply.github.com> Date: Wed, 1 Nov 2023 13:01:00 +0800 Subject: [PATCH] Update the argument description --- R/mfairGreedy.R | 2 +- man/fitGreedy.Rd | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/R/mfairGreedy.R b/R/mfairGreedy.R index 94b0be1..769f238 100644 --- a/R/mfairGreedy.R +++ b/R/mfairGreedy.R @@ -10,7 +10,7 @@ #' @param maxdepth Integer. Parameter for the gradient boosting part. #' @param other_tree_para A list containing other parameters for the gradient boosting part. See rpart::rpart.control() for details. #' @param tol_snr Numeric. The convergence criterion which determine the inferred rank of data. -#' @param null_check Logical. If TRUE, then mfair will check whether the current factor is close to zero. If the check is performed and successful, the factor will be deleted in the returned fit. +#' @param null_check Logical. If TRUE, then mfair will check whether the currently inferred factor is close to zero compared to the estimated noise strength. If the check is performed and successful, the factor will be deleted in the returned fit, and the greedy algorithm will be terminated. #' @param verbose_greedy Logical. Whether to display the detailed information when fitting the model. #' @param save_init Logical. Whether to save the initialization of the model. #' @param sf_para A list containing parameters for fitting the single factor MFAI model. See fitSFFully(), fitSFMissing(), or fitSFSparse() for details. diff --git a/man/fitGreedy.Rd b/man/fitGreedy.Rd index ffc7fd3..017382c 100644 --- a/man/fitGreedy.Rd +++ b/man/fitGreedy.Rd @@ -34,7 +34,7 @@ fitGreedy( \item{other_tree_para}{A list containing other parameters for the gradient boosting part. See rpart::rpart.control() for details.} -\item{null_check}{Logical. If TRUE, then mfair will check whether the current factor is close to zero. If the check is performed and successful, the factor will be deleted in the returned fit.} +\item{null_check}{Logical. If TRUE, then mfair will check whether the currently inferred factor is close to zero compared to the estimated noise strength. If the check is performed and successful, the factor will be deleted in the returned fit, and the greedy algorithm will be terminated.} \item{tol_snr}{Numeric. The convergence criterion which determine the inferred rank of data.}