v0.2.2 Updated documentation

samuel-watson · Jan 19, 2023 · 0878c7c · 0878c7c
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diff --git a/R/RcppExports.R b/R/RcppExports.R
@@ -17,7 +17,8 @@
 #' @param exp_cond Vector specifying the experimental condition index of each observation
 #' @param V0_list List of prior covariance matrices for the model parameters
 #' @param type Integer. 0 = local search algorithm. 1 = local+greedy+local. 2 = local+greedy. 3 = greedy+local
-#' @param rd_mode Integer. Robust objective function, 1=weighted average, 2=minimax
+#' @param robust_log Logical indicating to use a weighted sum of log (TRUE) or absolute (FALSE) values of the c-optimal 
+#' function when using a robust criterion.
 #' @param trace Logical indicating whether to provide detailed output
 #' @param uncorr Logical indicating whether to treat all the experimental conditions as uncorrelated (TRUE) or not (FALSE)
 #' @param bayes Logical indicating whether to use a Bayesian model with prior distributions on model parameters (TRUE) or a 

diff --git a/man/GradRobustStep.Rd b/man/GradRobustStep.Rd
diff --git a/src/gd_search.cpp b/src/gd_search.cpp
@@ -19,7 +19,7 @@
 //' @param exp_cond Vector specifying the experimental condition index of each observation
 //' @param V0_list List of prior covariance matrices for the model parameters
 //' @param type Integer. 0 = local search algorithm. 1 = local+greedy+local. 2 = local+greedy. 3 = greedy+local
-//' @param robust_log. Logical indicating to use a weighted sum of log (TRUE) or absolute (FALSE) values of the c-optimal 
+//' @param robust_log Logical indicating to use a weighted sum of log (TRUE) or absolute (FALSE) values of the c-optimal 
 //' function when using a robust criterion.
 //' @param trace Logical indicating whether to provide detailed output
 //' @param uncorr Logical indicating whether to treat all the experimental conditions as uncorrelated (TRUE) or not (FALSE)