jfa 0.6.0

NEWS.md

@@ -12,7 +12,7 @@
 
 **Major changes**
 
-- From `jfa` 0.5.7 to `jfa` 0.6.0 there has been a major overhaul in the names of function arguments. This is done so that the calls integrate better with general R syntax and the package gets more user-friendly. I apologive for any inconvenience this may cause. The following names have been changed:
+- From `jfa` 0.5.7 to `jfa` 0.6.0 there has been a major overhaul in the names of function arguments. This is done so that the calls integrate better with general R syntax and the package gets more user-friendly. I apologize for any inconvenience this may cause. The following names have been changed:
   - `median` -> `impartial` (in `auditPrior()`)
   - `sampleK` -> `x` (in `auditPrior()`)
   - `sampleN` -> `n` (in `auditPrior()`)

R/evaluation.R

@@ -30,7 +30,7 @@
 #' @param cs.a          if \code{method = "coxsnell"}, a numeric value specifying the \eqn{\alpha} parameter of the prior distribution on the mean taint. Defaults to 1 as recommended by Cox and Snell (1979).
 #' @param cs.b          if \code{method = "coxsnell"}, a numeric value specifying the \eqn{\beta} parameter of the prior distribution on the mean taint. Defaults to 3 as recommended by Cox and Snell (1979).
 #' @param cs.mu         if \code{method = "coxsnell"}, a numeric value between 0 and 1 specifying the mean of the prior distribution on the mean taint. Defaults to 0.5 as recommended by Cox and Snell (1979).
-#' @param prior         a logical specifying if a prior distribution must be used, or an object of class \code{jfaPrior} or \code{jfaPosterior} containing the prior distribution. Defaults to \code{FALSE} for frequentist planning. If \code{TRUE}, a noninformative prior distribution is chosen by default, but can be adjusted using the `kPrior` and `nPrior` arguments. Chooses a conjugate gamma distribution for the Poisson likelihood, a conjugate beta distribution for the binomial likelihood, and a conjugate beta-binomial distribution for the hypergeometric likelihood.
+#' @param prior         a logical specifying if a prior distribution must be used, or an object of class \code{jfaPrior} or \code{jfaPosterior} containing the prior distribution. Defaults to \code{FALSE} for frequentist planning. If \code{TRUE}, a minimal information prior is chosen by default. Chooses a conjugate gamma distribution for the Poisson likelihood, a conjugate beta distribution for the binomial likelihood, and a conjugate beta-binomial distribution for the hypergeometric likelihood.
 #'
 #' @details This section lists the available options for the \code{methods} argument.
 #'

R/planning.R

@@ -16,7 +16,7 @@
 #' @param likelihood    a character specifying the likelihood assumed in the calculation. This can be either \code{poisson} (default) for the Poisson likelihood, \code{binomial} for the binomial likelihood, or \code{hypergeometric} for the hypergeometric likelihood. See the details section for more information about the available likelihoods.
 #' @param conf.level    a numeric value between 0 and 1 specifying the confidence level used in the planning. Defaults to 0.95 for 95\% confidence.
 #' @param N.units       an integer larger than 0 specifying the total number of units or items in the population (i.e., the population size). Only required when \code{likelihood = 'hypergeometric'}.
-#' @param prior         a logical specifying whether to use a prior distribution when planning, or an object of class \code{jfaPrior} or \code{jfaPosterior} containing the prior distribution. Defaults to \code{FALSE} for frequentist planning. If \code{TRUE}, a noninformative prior distribution is used. Chooses a conjugate gamma distribution for the Poisson likelihood, a conjugate beta distribution for the binomial likelihood, and a conjugate beta-binomial distribution for the hypergeometric likelihood.
+#' @param prior         a logical specifying whether to use a prior distribution when planning, or an object of class \code{jfaPrior} or \code{jfaPosterior} containing the prior distribution. Defaults to \code{FALSE} for frequentist planning. If \code{TRUE}, a minimal information prior is chosen by default. Chooses a conjugate gamma distribution for the Poisson likelihood, a conjugate beta distribution for the binomial likelihood, and a conjugate beta-binomial distribution for the hypergeometric likelihood.
 #' @param by            an integer larger than 0 specifying the desired increment for the sample size calculation.
 #' @param max           an integer larger than 0 specifying the maximum sample size that is considered in the calculation. Defaults to 5000 for efficiency. Increase this value if the sample size cannot be found due to it being too large (e.g., for a low materiality).
 #'