added BCEA:: to evppi() calls in @examples so doesnt clash with voi v…

…ersion of evppi()

R/evppi.R

@@ -161,26 +161,27 @@
 #' # Compute the EVPPI for a bunch of parameters
 #' inp <- createInputs(vaccine_mat)
 #' 
-#' EVPPI <- evppi(m, c("beta.1." , "beta.2."), inp$mat)
+#' # explicitly use BCEA package namespace to avoid voi package conflict
+#' EVPPI <- BCEA::evppi(m, c("beta.1." , "beta.2."), inp$mat)
 #' 
 #' plot(EVPPI)
 #' 
 #' # deprecated (single parameter) methods
-#' EVPPI.so <- evppi(m, c("beta.1.", "beta.2."), inp$mat, method = "so", n.blocks = 50)
-#' EVPPI.sad <- evppi(m, c("beta.1.", "beta.2."), inp$mat, method = "sad", n.seps = 1)
+#' EVPPI.so <- BCEA::evppi(m, c("beta.1.", "beta.2."), inp$mat, method = "so", n.blocks = 50)
+#' EVPPI.sad <- BCEA::evppi(m, c("beta.1.", "beta.2."), inp$mat, method = "sad", n.seps = 1)
 #' 
 #' plot(EVPPI.so)
 #' plot(EVPPI.sad)
 #'  
 #' # Compute the EVPPI using INLA/SPDE
 #' if (require("INLA"))
-#'   x_inla <- evppi(he = m, 39:40, input = inp$mat)
+#'   x_inla <- BCEA::evppi(he = m, 39:40, input = inp$mat)
 #' 
 #' # using GAM regression
-#' x_gam <- evppi(he = m, 39:40, input = inp$mat, method = "GAM")
+#' x_gam <- BCEA::evppi(he = m, 39:40, input = inp$mat, method = "GAM")
 #' 
 #' # using Strong et al GP regression
-#' x_gp <- evppi(he = m, 39:40, input = inp$mat, method = "GP")
+#' x_gp <- BCEA::evppi(he = m, 39:40, input = inp$mat, method = "GP")
 #' 
 #' # plot results
 #' if (require("INLA")) plot(x_inla)
@@ -199,7 +200,7 @@
 #' "Individual counselling", "Group counselling")
 #' m <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)
 #' inp <- createInputs(smoking_output)
-#' EVPPI <- evppi(m, c(2,3), inp$mat, h.value = 0.0000005)
+#' EVPPI <- BCEA::evppi(m, c(2,3), inp$mat, h.value = 0.0000005)
 #' plot(EVPPI)
 #' }
 #' 

R/evppi.default.R

@@ -14,7 +14,8 @@ evppi.default <- function(he, ...) {
 #' treats <- c("Status quo", "Vaccination")
 #' bcea_vacc <- bcea(e.pts, c.pts, ref = 2, interventions = treats)
 #' inp <- createInputs(vaccine_mat)
-#' evppi(bcea_vacc, c("beta.1.", "beta.2."), inp$mat)
+#' BCEA::evppi(bcea_vacc, c("beta.1.", "beta.2."), inp$mat)
+#' 
 #' @export
 #' 
 evppi.bcea <- function(he,

R/inforank_params.R

@@ -77,10 +77,10 @@ inforank_params <- function(he,
   for (i in seq_along(chk2)) {
     x[[i]] <-
       quiet(
-        evppi(he = m,
-              param_idx = chk2[i],
-              input = input,
-              N = N))
+        BCEA::evppi(he = m,
+                    param_idx = chk2[i],
+                    input = input,
+                    N = N))
   }
 
   scores <- 

R/plot.evppi.R

@@ -38,11 +38,11 @@
 #' 
 #' # Compute the EVPPI using INLA/SPDE
 #' if (require("INLA")) {
-#'   x0 <- evppi(m, c("beta.1." , "beta.2."), input = inp$mat)
+#'   x0 <- BCEA::evppi(m, c("beta.1." , "beta.2."), input = inp$mat)
 #'   
 #'   plot(x0, pos = c(0,1))
 #' 
-#'   x1 <- evppi(m, c(32,48,49), input = inp$mat)
+#'   x1 <- BCEA::evppi(m, c(32,48,49), input = inp$mat)
 #'   plot(x1, pos = "topright")
 #' 
 #'   plot(x0, col = c("black", "red"), pos = "topright")