run docs

.lintr

@@ -1,5 +1,6 @@
 linters: with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
-  object_usage_linter = NULL
+  object_usage_linter = NULL,
+  object_name_linter = NULL
   )

DESCRIPTION

@@ -35,7 +35,7 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.0
+RoxygenNote: 7.2.3
 Collate:
     'Phase1b-package.R'
     'betadiff.R'

R/dbetabinom.R

@@ -127,8 +127,8 @@ dbetaMix <- Vectorize(dbetaMix, vectorize.args = "x")
 ##' @param par the beta parameters matrix, with K rows and 2 columns,
 ##' corresponding to the beta parameters of the K components
 ##' @param weights the mixture weights of the beta mixture prior
-##' @param lower.tail logical; if TRUE (default), probabilities are P[X <= x],
-##' and otherwise P[X > x]
+##' @param lower.tail logical; if TRUE (default), probabilities are `P[X <= x]`,
+##' and otherwise `P[X > x]`
 ##' @return the (one minus) cdf value
 ##'
 ##' @export

R/plotBounds.R

@@ -15,8 +15,8 @@
 ##' @param yt  indicate the y axis: response rate is "p", number of responses
 ##' is "x"
 ##' @param add  add the boundary lines or not
-##' @param cols specific the color of [1] efficacy area [2] futility area
-##' [3] efficacy boundary [4] futility boundary
+##' @param cols specific the color of `[1]` efficacy area `[2]` futility area
+##' `[3]` efficacy boundary `[4]` futility boundary
 ##' @param lwds line width (a two dimensional vector)
 ##' @param ltype line type
 ##' @param lpch  a value of plotting characters or symbols

R/postprob.R

@@ -29,9 +29,9 @@ postprobOld <- function(x, n, p, a = 1, b = 1) {
 ##' Compute the posterior probability to be above threshold,
 ##' with a beta mixture prior on the response rate.
 ##'
-##' Computes the posterior probability Pr(P_E > p | data). Prior is P_E ~
-##' sum(weights * beta(parE[, 1], parE[, 2])), i.e., a mixture of beta priors.
-##' Default is one component only with uniform or beta(1,1).
+##' Computes the posterior probability `Pr(P_E > p | data)`. Prior is
+##' `P_E ~ sum(weights * beta(parE[, 1], parE[, 2]))`, i.e., a mixture of beta priors.
+##' Default is one component only with uniform or `beta(1,1)`.
 ##'
 ##' We observed x successes in n trials. Note that \code{x} can be a vector.
 ##'