96 bounds predprob

R/boundsPredprob.R

@@ -52,7 +52,7 @@ boundsPredprob <- function(looks, Nmax = max(looks), p0, tT, phiL, phiU, parE =
   if (missing(weights)) {
     weights <- rep(1, nrow(t(parE)))
   }
-  assert_numeric(weights, min.len = 0, len = nrow(par), finite = TRUE)
+  assert_numeric(weights, min.len = 0, len = nrow(parE), finite = TRUE)
   for (n in looks) {
     k <- k + 1
     # initialize so will return NA if 0 or n in "continue" region

R/postprob.R

@@ -55,7 +55,7 @@ postprobBeta <- function(x, n, p, a = 1, b = 1) {
 #'  threshold that `P_E` is measured.
 #' @typed parE : matrix
 #'  the beta parameters matrix, with `K` rows and 2 columns,
-#'  corresponding to the beta parameters of the `K` priors.
+#'  corresponding to the beta parameters of the `K` components.
 #' @typed weights : vector
 #'  The mixture weights of the beta mixture prior.
 #' @typed betamixPost : matrix

R/predprob.R

@@ -31,7 +31,7 @@
 #'  threshold on the probability to be above p.
 #' @typed parE : numeric
 #'  the beta parameters matrix, with K rows and 2 columns,
-#'  corresponding to the beta parameters of the K priors.
+#'  corresponding to the beta parameters of the K components.
 #' @typed weights : numeric
 #'  the mixture weights of the beta mixture prior.
 #' @return A `list` is returned with names `result` for predictive probability and