added n(s)ec to compare_* functions

DESCRIPTION

@@ -2,7 +2,7 @@ Package: bayesnec
 Title: A Bayesian No-Effect- Concentration (NEC) Algorithm
 Version: 2.1.0.3
 Authors@R: c(person("Rebecca", "Fisher", email = "r.fisher@aims.gov.au", role = c("aut", "cre")), person("Diego","Barneche",role="aut"), person("Gerard","Ricardo",role="aut"), person("David","Fox",role="aut"))
-Description: Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>), 'NSEC' (see Fisher and Fox (2023)<10.1002/etc.5610>), and 'N(S)EC (see Fisher et al. 2023<10.1002/ieam.4809>). This package expands and supersedes an original version implemented in R2jags, see Fisher, Ricardo and Fox (2020)<doi:10.5281/ZENODO.3966864>.
+Description: Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECx' values, but more particularly 'NEC' (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>), 'NSEC' (see Fisher and Fox (2023)<doi:10.1002/etc.5610>), and 'N(S)EC (see Fisher et al. 2023<doi:10.1002/ieam.4809>). This package expands and supersedes an original version implemented in R2jags, see Fisher, Ricardo and Fox (2020)<doi:10.5281/ZENODO.3966864>.
 Depends:
     R (>= 4.1),
     brms,

R/compare_estimates.R

@@ -31,11 +31,11 @@
 #' }
 #'
 #' @export
-compare_estimates <- function(x, comparison = "nec", ecx_val = 10,
+compare_estimates <- function(x, comparison = "n(s)ec", ecx_val = 10,
                               type = "absolute", hormesis_def = "control",
                               sig_val = 0.01, resolution = 100, x_range = NA) {
-  if ((comparison %in% c("nec", "ecx", "nsec")) == FALSE) {
-    stop("comparison must be one of nec, ecx or nsec.")
+  if ((comparison %in% c("nec", "n(s)ec", "ecx", "nsec")) == FALSE) {
+    stop("comparison must be one of nec, n(s)ec, ecx or nsec.")
   }
   chk_numeric(ecx_val)
   if ((type %in% c("relative", "absolute", "direct")) == FALSE) {
@@ -54,6 +54,9 @@ compare_estimates <- function(x, comparison = "nec", ecx_val = 10,
     chk_numeric(x_range)    
   }
   if (comparison == "nec") {
+    posterior_list <- lapply(x, nec, posterior = TRUE, xform = identity)
+  }
+  if (comparison == "n(s)ec") {
     posterior_list <- lapply(x, return_nec_post, xform = identity)
   }
   if (comparison == "ecx") {

R/compare_posterior.R

@@ -8,7 +8,7 @@
 #' \code{\link{bayesnecfit}} or \code{\link{bayesmanecfit}} returned by
 #' \code{\link{bnec}}.
 #' @param comparison The posterior predictions to compare, takes values of
-#' "nec", "nsec", "ecx" or "fitted".
+#' "nec", "n(s)ec", "nsec", "ecx" or "fitted".
 #' @param make_newdata Only used if \code{comparison = "fitted"}. Should the
 #' user allow the package to create \code{newdata} for predictions?
 #' If so, arguments \code{resolution} and \code{x_range} will be used. Defaults
@@ -59,11 +59,11 @@
 #' data(manec_example)
 #' nec4param <- pull_out(manec_example, model = "nec4param")
 #' ecx4param <- pull_out(manec_example, model = "ecx4param")
-#' compare_posterior(list("nec" = ecx4param, "ecx" = nec4param), ecx_val = 50)
+#' compare_posterior(list("n(s)ec" = ecx4param, "ecx" = nec4param), ecx_val = 50)
 #' }
 #'
 #' @export
-compare_posterior <- function(x, comparison = "nec", ecx_val = 10,
+compare_posterior <- function(x, comparison = "n(s)ec", ecx_val = 10,
                               type = "absolute", hormesis_def = "control",
                               sig_val = 0.01, resolution, x_range = NA,
                               make_newdata = TRUE, ...) {