diff --git a/NAMESPACE b/NAMESPACE
index ddd1076..201d55f 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -6,12 +6,14 @@ export(geo_mean)
 export(get_bayes_R2)
 export(get_coefs)
 export(get_coefs_raw)
+export(get_first_term)
 export(get_index)
 export(get_influ)
 export(get_influ2)
 export(get_marginal)
 export(get_unstandarsied)
 export(id_var_type)
+export(influ_app)
 export(inv_logit)
 export(logistic)
 export(logit)
@@ -34,7 +36,9 @@ import(dplyr)
 import(ggplot2)
 import(patchwork)
 import(proto)
+import(shiny)
 importFrom(brms,add_criterion)
+importFrom(brms,is.brmsfit)
 importFrom(brms,posterior_samples)
 importFrom(gtable,gtable_filter)
 importFrom(gtable,is.gtable)
diff --git a/R/app.R b/R/app.R
new file mode 100644
index 0000000..70a67ab
--- /dev/null
+++ b/R/app.R
@@ -0,0 +1,42 @@
+#' Run shiny application
+#' 
+#' @param fits a list of objects of class \code{brmsfit} that you want to compare.
+#' @return a \code{shiny.appobj} object.
+#' @import shiny
+#' @export
+#' 
+influ_app <- function(fits) {
+  
+  n <- length(fits)
+  flabs <- rep(NA, n)
+  
+  for (i in 1:n) {
+    str <- as.character(fits[[i]]$formula)[1]
+    left1 <- stringi::stri_trim_right(str = str, pattern = "[\u007E]", negate = FALSE)
+    flabs[i] <- substr(x = str, nchar(left1) + 2, nchar(str))
+  }
+  
+  ui <- navbarPage(
+    title = "influ2",
+    tabPanel(
+      title = "Model comparisons",
+      tableOutput(outputId = "table_cf"),
+      selectInput(inputId = "pick_fits", label = "Select the fits", choices = flabs, selected = flabs, multiple = TRUE),
+      plotOutput(outputId = "plot_cf", click = "plot_click")
+    )
+  )
+  
+  server <- function(input, output, session) {
+    output$table_cf <- renderTable({
+      get_bayes_R2(fits = fits)
+    })
+    output$plot_cf <- renderPlot({
+      ii <- which(input$pick_fits %in% flabs)
+      ifits <- fits[ii]
+      plot_compare(fits = ifits)
+    })
+  }
+  
+  shinyApp(ui = ui, server = server)
+  # shinyApp(ui = ui, server = server, ...)
+}
diff --git a/R/get-index.R b/R/get-index.R
index 632c886..ef87ea8 100644
--- a/R/get-index.R
+++ b/R/get-index.R
@@ -1,43 +1,21 @@
-#' Logit
-#' 
-#' @inheritParams stats::qlogis
-#' @return the density.
-#' @importFrom stats qlogis
-#' @export
-#' 
-logit <- function(p, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) {
-  qlogis(p = p, location = location, scale = scale, lower.tail = lower.tail, log.p = log.p)
-}
-
-
-#' Logistic
-#' 
-#' @param q vector of quantiles.
-#' @inheritParams stats::plogis
-#' @param log.p logical; if TRUE, probabilities p are given as log(p).
-#' @return gives the distribution function.
-#' @importFrom stats plogis
-#' @export
-#' 
-logistic <- function(q, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) {
-  plogis(q = q, location = location, scale = scale, lower.tail = lower.tail, log.p = log.p)
-}
-
-
 #' Get the unstandardised indices
 #' 
 #' @param fit An object of class \code{brmsfit}.
 #' @param year The year or time label (e.g. year, Year, fishing_year, etc).
 #' @param rescale How to re-scale the series. Choose from "raw" to retain the raw unstandardised series, or a number to re-scale by. 
 #' @return a \code{data.frame} or a \code{ggplot} object.
-#' @import brms
+#' @importFrom brms is.brmsfit
 #' @import dplyr
 #' @export
 #' 
-get_unstandarsied <- function(fit, year = "year", rescale = 1) {
+get_unstandarsied <- function(fit, year = NULL, rescale = 1) {
 
   if (!is.brmsfit(fit)) stop("fit is not an object of class brmsfit.")
   
+  if (is.null(year)) {
+    year <- get_first_term(fit = fit)
+  }
+  
   if (fit$family$family %in% c("bernoulli", "negbinomial") | grepl("hurdle", fit$family$family)) {
     prop <- data.frame(y = fit$data[,1], Year = fit$data[,year]) %>%
       mutate(y = ifelse(.data$y > 0, 1, 0)) %>%
@@ -84,20 +62,21 @@ get_unstandarsied <- function(fit, year = "year", rescale = 1) {
 #' @param do_plot Return a \code{ggplot} object instead of a \code{data.frame}.
 #' @param ... Additional parameters passed to \code{fitted}.
 #' @return a \code{data.frame} or a \code{ggplot} object.
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @importFrom stats fitted
-#' @import brms
+#' @importFrom brms is.brmsfit
 #' @import ggplot2
 #' @import patchwork
 #' @import dplyr
 #' @export
 #' 
-get_index <- function(fit, year = "year", probs = c(0.025, 0.975), rescale = 1, do_plot = FALSE, ...) {
+get_index <- function(fit, year = NULL, probs = c(0.025, 0.975), rescale = 1, do_plot = FALSE, ...) {
   
   if (!is.brmsfit(fit)) stop("fit is not an object of class brmsfit.")
   
+  if (is.null(year)) {
+    year <- get_first_term(fit = fit)
+  }
+  
   # std <- get_coefs(fit = fit, var = year)
   yrs <- sort(unique(fit$data[,year]))
   n <- length(yrs)
@@ -120,22 +99,6 @@ get_index <- function(fit, year = "year", probs = c(0.025, 0.975), rescale = 1,
   }
   newdata[,year] <- yrs
   newdata$pots <- 1
-
-  # fout1 <- fitted(object = fit, newdata = newdata, probs = c(probs[1], 0.5, probs[2]), re_formula = NA)
-  # newdata <- newdata[,1:5]
-  # newdata <- expand.grid(cpue = 1, period = unique(celr5$period), area2 = NA, vessel = NA, month = NA, "period:area2" = NA)
-  # names(newdata) <- names(fit5$data)
-  # head(fit$data)
-  # head(newdata)
-  # fout1 <- fitted(object = fit, newdata = newdata)
-  # fout1 <- fitted(object = fit4, newdata = newdata, probs = c(probs[1], 0.5, probs[2]))
-  # fout1 <- conditional_effects(x = fit, effects = "period")[[1]]
-  # conditions <- data.frame(area2 = c("916", "917", "933"))
-  # fout1 <- conditional_effects(x = fit, effects = "period", conditions = conditions)[[1]]
-  # fout1 <- posterior_epred(object = fit, newdata = newdata, probs = c(probs[1], 0.5, probs[2]))
-  # fout1 <- posterior_predict(object = fit, newdata = newdata)
-  # fout1 <- fitted(object = fit)
-  # pred1 <- predict(fit, newdata = newdata, re_formula = NULL, allow_new_levels = TRUE)
   
   # Get the predicted CPUE by year
   fout1 <- fitted(object = fit, newdata = newdata, probs = c(probs[1], 0.5, probs[2]), re_formula = NA) %>% 
diff --git a/R/helper-functions.R b/R/helper-functions.R
index ee69f21..58b6f02 100644
--- a/R/helper-functions.R
+++ b/R/helper-functions.R
@@ -57,15 +57,54 @@ glm_step_plot <- function(data, mod_list, ibest = 5) {
 }
 
 
+#' Get first model term
+#' 
+#' @param fit An object of class \code{brmsfit}.
+#' @return the first model term
+#' @importFrom brms is.brmsfit
+#' @export
+#' 
+get_first_term <- function(fit) {
+  if (!is.brmsfit(fit)) stop("fit is not an object of class brmsfit.")
+  f1 <- as.character(fit$formula)[1]
+  f2 <- gsub("~", "+", f1)
+  f3 <- str_split(f2, " \\+ ")[[1]]
+  return(f3[2])
+}
+
+
+#' Logit
+#' 
+#' @inheritParams stats::qlogis
+#' @return the density.
+#' @importFrom stats qlogis
+#' @export
+#' 
+logit <- function(p, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) {
+  qlogis(p = p, location = location, scale = scale, lower.tail = lower.tail, log.p = log.p)
+}
+
+
+#' Logistic
+#' 
+#' @param q vector of quantiles.
+#' @inheritParams stats::plogis
+#' @param log.p logical; if TRUE, probabilities p are given as log(p).
+#' @return gives the distribution function.
+#' @importFrom stats plogis
+#' @export
+#' 
+logistic <- function(q, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) {
+  plogis(q = q, location = location, scale = scale, lower.tail = lower.tail, log.p = log.p)
+}
+
+
 #' Identify the variable type
 #' 
 #' @param fit An object of class \code{brmsfit}.
 #' @param xfocus the x
 #' @param hurdle if hurdle or not
 #' @return The geometric mean of the vector.
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @export
 #' 
 id_var_type <- function(fit, xfocus, hurdle = FALSE) {
@@ -106,9 +145,6 @@ id_var_type <- function(fit, xfocus, hurdle = FALSE) {
 #' 
 #' @param a a vector.
 #' @return The geometric mean of the vector.
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @export
 #' 
 geo_mean <- function(a) {
@@ -119,7 +155,6 @@ geo_mean <- function(a) {
 #' Inverse logit
 #' 
 #' @param a a vector.
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
 #' @export
 #' 
 inv_logit <- function(a) {
@@ -130,7 +165,6 @@ inv_logit <- function(a) {
 #' logit
 #' 
 #' @param p a vector.
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
 #' @export
 #' 
 logit <- function(p) {
diff --git a/R/plot-compare.R b/R/plot-compare.R
index 8028867..16bcd18 100644
--- a/R/plot-compare.R
+++ b/R/plot-compare.R
@@ -16,7 +16,7 @@
 #' @importFrom stringi stri_trim_right
 #' @export
 #' 
-plot_compare <- function(fits, labels = NULL, year = "year", 
+plot_compare <- function(fits, labels = NULL, year = NULL, 
                          probs = c(0.25, 0.75), show_probs = TRUE, 
                          rescale = "raw", rescale_series = NULL) {
   
@@ -27,7 +27,7 @@ plot_compare <- function(fits, labels = NULL, year = "year",
     if (is.null(labels)) {
       str <- as.character(fits[[i]]$formula)[1]
       left1 <- stri_trim_right(str = str, pattern = "[\u007E]", negate = FALSE)
-      fout$Model <- substr(str, nchar(left1) + 2, nchar(str))
+      fout$Model <- substr(x = str, nchar(left1) + 2, nchar(str))
     } else {
       fout$Model <- labels[i]
     }
diff --git a/R/plot-index.R b/R/plot-index.R
index 6f75d8d..858da61 100644
--- a/R/plot-index.R
+++ b/R/plot-index.R
@@ -9,9 +9,6 @@
 #' @param rescale the index of the series to rescale to. If set to NULL then no rescaling is done.
 #' @param show_unstandardised show the unstandardised series or not.
 #' @return a \code{ggplot} object.
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @importFrom stats fitted
 #' @import brms
 #' @import ggplot2
@@ -19,14 +16,18 @@
 #' @export
 #' 
 plot_index <- function(fit, 
-                       year = "Year", 
+                       year = NULL, 
                        fill = "purple", 
                        probs = c(0.25, 0.75),
                        rescale = 1,
                        show_unstandardised = TRUE) {
   
   if (!is.brmsfit(fit)) stop("fit is not an object of class brmsfit.")
-
+  
+  if (is.null(year)) {
+    year <- get_first_term(fit = fit)
+  }
+  
   # Get the standardised series
   fout <- get_index(fit = fit, year = year, probs = probs, rescale = rescale) %>%
     mutate(model = "Standardised")
diff --git a/R/plot-influ.R b/R/plot-influ.R
index e0873e4..2af940e 100644
--- a/R/plot-influ.R
+++ b/R/plot-influ.R
@@ -7,11 +7,7 @@
 #' @param fill the colour to use in the plot.
 #' @param hurdle if a hurdle model then use the hurdle
 #' @return a \code{ggplot} object.
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @seealso \code{\link{get_influ}}
-#' 
 #' @examples
 #' \dontrun{
 #' data(epilepsy)
@@ -20,14 +16,18 @@
 #' summary(fit1)
 #' plot_influ(fit = fit1, year = "Age")
 #' }
-#' 
+#' @importFrom brms is.brmsfit
 #' @import ggplot2
 #' @export
 #' 
-plot_influ <- function(fit, year = "fishing_year", fill = "purple", hurdle = FALSE) {
+plot_influ <- function(fit, year = NULL, fill = "purple", hurdle = FALSE) {
   
   if (!is.brmsfit(fit)) stop("fit is not an object of class brmsfit.")
   
+  if (is.null(year)) {
+    year <- get_first_term(fit = fit)
+  }
+  
   # Extract the models variable names
   # x1 <- gsub(paste0(as.character(fit$formula)[4], " ~ "), "", as.character(fit$formula)[1])
   # x2 <- strsplit(x1, split = " + ", fixed = TRUE)[[1]]
diff --git a/R/plot-step.R b/R/plot-step.R
index 3551b33..17b7078 100644
--- a/R/plot-step.R
+++ b/R/plot-step.R
@@ -7,15 +7,12 @@
 #' @param fill the colour of the credible interval ribbon
 #' @param probs the quantiles to plot
 #' @param show_probs plot the quantiles or not
-#' 
-#' @author Darcy Webber \email{darcy@quantifish.co.nz}
-#' 
 #' @import brms
 #' @import ggplot2
 #' @import dplyr
 #' @export
 #' 
-plot_step <- function(fits, year = "year", fill = "purple",
+plot_step <- function(fits, year = NULL, fill = "purple",
                       probs = c(0.25, 0.75), show_probs = TRUE) {
   
   m <- length(fits)
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 53b7eb0..106bf45 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -10,6 +10,28 @@ navbar:
     right: [search, github]
 
 reference:
+- title: influ2 functions
+  desc: Functions from the new influ2 R package.
+  contents:
+  - influ2
+  - starts_with("get_")
+  - logit
+  - inv_logit
+  - logistic
+  - id_var_type
+  - geo_mean
+
+- title: influ2 plots
+  desc: Plots and tables from the new influ2 R package.
+  contents:
+  - starts_with("plot_")
+  - starts_with("table_")
+
+- title: Data
+  desc: Simulated data sets that are available.
+  contents:
+  - lobsters_per_pot
+
 - title: influ
   desc: Functions from the original influ R package.
   contents:
@@ -27,21 +49,4 @@ reference:
   - Influence$stepAndInfluPlot
   - coeffs
   - ses
-
-- title: influ2
-  desc: Functions from the new influ2 R package.
-  contents:
-  - influ2
-  - starts_with("get_")
-  - starts_with("plot_")
-  - starts_with("table_")
-  - logit
-  - inv_logit
-  - logistic
-  - id_var_type
-  - geo_mean
-
-- title: Data
-  desc: Simulated data sets that are available.
-  contents:
-  - lobsters_per_pot
+  
\ No newline at end of file
diff --git a/man/geo_mean.Rd b/man/geo_mean.Rd
index 7a1282c..01bcfad 100644
--- a/man/geo_mean.Rd
+++ b/man/geo_mean.Rd
@@ -15,6 +15,3 @@ The geometric mean of the vector.
 \description{
 Geometric mean
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/get_first_term.Rd b/man/get_first_term.Rd
new file mode 100644
index 0000000..fc67b29
--- /dev/null
+++ b/man/get_first_term.Rd
@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/helper-functions.R
+\name{get_first_term}
+\alias{get_first_term}
+\title{Get first model term}
+\usage{
+get_first_term(fit)
+}
+\arguments{
+\item{fit}{An object of class \code{brmsfit}.}
+}
+\value{
+the first model term
+}
+\description{
+Get first model term
+}
diff --git a/man/get_index.Rd b/man/get_index.Rd
index 6ad760e..0e89ad1 100644
--- a/man/get_index.Rd
+++ b/man/get_index.Rd
@@ -6,7 +6,7 @@
 \usage{
 get_index(
   fit,
-  year = "year",
+  year = NULL,
   probs = c(0.025, 0.975),
   rescale = 1,
   do_plot = FALSE,
@@ -32,6 +32,3 @@ a \code{data.frame} or a \code{ggplot} object.
 \description{
 Get the standardised indices each year with associated uncertainty and return either as a table or a ggplot.
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/get_unstandarsied.Rd b/man/get_unstandarsied.Rd
index 4030441..3a2b2ff 100644
--- a/man/get_unstandarsied.Rd
+++ b/man/get_unstandarsied.Rd
@@ -4,7 +4,7 @@
 \alias{get_unstandarsied}
 \title{Get the unstandardised indices}
 \usage{
-get_unstandarsied(fit, year = "year", rescale = 1)
+get_unstandarsied(fit, year = NULL, rescale = 1)
 }
 \arguments{
 \item{fit}{An object of class \code{brmsfit}.}
diff --git a/man/id_var_type.Rd b/man/id_var_type.Rd
index 8a503cc..75ec724 100644
--- a/man/id_var_type.Rd
+++ b/man/id_var_type.Rd
@@ -19,6 +19,3 @@ The geometric mean of the vector.
 \description{
 Identify the variable type
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/influ_app.Rd b/man/influ_app.Rd
new file mode 100644
index 0000000..b42e17c
--- /dev/null
+++ b/man/influ_app.Rd
@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/app.R
+\name{influ_app}
+\alias{influ_app}
+\title{Run shiny application}
+\usage{
+influ_app(fits)
+}
+\arguments{
+\item{fits}{a list of objects of class \code{brmsfit} that you want to compare.}
+}
+\value{
+a \code{shiny.appobj} object.
+}
+\description{
+Run shiny application
+}
diff --git a/man/inv_logit.Rd b/man/inv_logit.Rd
index 869e858..a67392b 100644
--- a/man/inv_logit.Rd
+++ b/man/inv_logit.Rd
@@ -12,6 +12,3 @@ inv_logit(a)
 \description{
 Inverse logit
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/logistic.Rd b/man/logistic.Rd
index 7dbcda2..e0b3df8 100644
--- a/man/logistic.Rd
+++ b/man/logistic.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/get-index.R
+% Please edit documentation in R/helper-functions.R
 \name{logistic}
 \alias{logistic}
 \title{Logistic}
diff --git a/man/logit.Rd b/man/logit.Rd
index abcb40b..3a55a3a 100644
--- a/man/logit.Rd
+++ b/man/logit.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/get-index.R, R/helper-functions.R
+% Please edit documentation in R/helper-functions.R
 \name{logit}
 \alias{logit}
 \title{Logit}
@@ -19,6 +19,3 @@ Logit
 
 logit
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/plot_compare.Rd b/man/plot_compare.Rd
index fe97458..a02021c 100644
--- a/man/plot_compare.Rd
+++ b/man/plot_compare.Rd
@@ -7,7 +7,7 @@
 plot_compare(
   fits,
   labels = NULL,
-  year = "year",
+  year = NULL,
   probs = c(0.25, 0.75),
   show_probs = TRUE,
   rescale = "raw",
diff --git a/man/plot_index.Rd b/man/plot_index.Rd
index c4f8331..8c6ef95 100644
--- a/man/plot_index.Rd
+++ b/man/plot_index.Rd
@@ -6,7 +6,7 @@
 \usage{
 plot_index(
   fit,
-  year = "Year",
+  year = NULL,
   fill = "purple",
   probs = c(0.25, 0.75),
   rescale = 1,
@@ -32,6 +32,3 @@ a \code{ggplot} object.
 \description{
 In this plot the unstandardised indices is the geometric mean of the data.
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/plot_influ.Rd b/man/plot_influ.Rd
index b03716f..5dd766e 100644
--- a/man/plot_influ.Rd
+++ b/man/plot_influ.Rd
@@ -4,7 +4,7 @@
 \alias{plot_influ}
 \title{Plot the influence metric for all variables in a model}
 \usage{
-plot_influ(fit, year = "fishing_year", fill = "purple", hurdle = FALSE)
+plot_influ(fit, year = NULL, fill = "purple", hurdle = FALSE)
 }
 \arguments{
 \item{fit}{An object of class \code{brmsfit}.}
@@ -29,11 +29,7 @@ fit1 <- brm(count ~ Age + (1|patient), data = epilepsy, family = poisson(), iter
 summary(fit1)
 plot_influ(fit = fit1, year = "Age")
 }
-
 }
 \seealso{
 \code{\link{get_influ}}
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/man/plot_step.Rd b/man/plot_step.Rd
index aa2c7ff..fc3be9f 100644
--- a/man/plot_step.Rd
+++ b/man/plot_step.Rd
@@ -6,7 +6,7 @@
 \usage{
 plot_step(
   fits,
-  year = "year",
+  year = NULL,
   fill = "purple",
   probs = c(0.25, 0.75),
   show_probs = TRUE
@@ -26,6 +26,3 @@ plot_step(
 \description{
 This requires that all steps be run using brms and then provided as a list of model fits.
 }
-\author{
-Darcy Webber \email{darcy@quantifish.co.nz}
-}
diff --git a/vignettes/influ2.Rmd b/vignettes/influ2.Rmd
index a107d80..4963e5e 100644
--- a/vignettes/influ2.Rmd
+++ b/vignettes/influ2.Rmd
@@ -56,7 +56,7 @@ theme_set(theme_bw())
 options(mc.cores = 2)
 ```
 
-The simulated data set
+The simulated data set:
 
 ```{r sim-data, echo=TRUE, message=FALSE}
 data(lobsters_per_pot)
@@ -131,11 +131,11 @@ be modelled separately and then a list of models defined as below.
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE, fig.cap = "The new Bayesian step-plot from the influ2 package. Note that the new step-plot requires that all models/steps be run in brms before the function can be used."}
 fits <- list(fit1, fit2)
-plot_step(fits = fits, year = "year")
+plot_step(fits = fits)
 ```
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE}
-plot_index(fit2, year = "year")
+plot_index(fit = fit2)
 ```
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE}
@@ -143,7 +143,7 @@ myInfl$stanPlot()
 ```
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE}
-plot_influ(fit = fit1, year = "year")
+plot_influ(fit = fit1)
 ```
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE}
@@ -217,11 +217,11 @@ plot_bayesian_cdi(fit = fit2, xfocus = "month", yfocus = "year",
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE, fig.cap = "Comparison plot of all model runs."}
 fits <- list(fit1, fit2)
-plot_compare(fits = fits, year = "year")
+plot_compare(fits = fits)
 ```
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE, fig.cap = "Unstandardised versus standardised series."}
-plot_index(fit = fit1, year = "year")
+plot_index(fit = fit1)
 ```
 
 # Diagnostics
@@ -312,8 +312,8 @@ can be produced using the `get_index` function. The `Estimate` and `Est.Error`
 columns are what should be used in stock assessment.
 
 ```{r echo=TRUE, fig.height=6, fig.width=6, message=FALSE}
-unstd <- get_unstandarsied(fit = fit2, year = "year")
-cpue0 <- get_index(fit = fit2, year = "year")
+unstd <- get_unstandarsied(fit = fit2)
+cpue0 <- get_index(fit = fit2)
 
 cpue0 %>%
   mutate(Unstandardised = unstd$Median) %>%
@@ -349,9 +349,8 @@ for (ii in 1:nrow(cpue1)) {
   cpue3$Qupper[ii] <- quantile(r1, probs = 0.975)
 }
 
-df <- bind_rows(cpue1, cpue2, cpue3)
-
-ggplot(data = df, aes(x = Year, y = Median, colour = Type)) +
+ggplot(data = bind_rows(cpue1, cpue2, cpue3), 
+       aes(x = Year, y = Median, colour = Type)) +
   geom_pointrange(aes(ymin = Qlower, ymax = Qupper), 
                   position = position_dodge(width = 0.5)) +
   scale_y_continuous(limits = c(0, NA), expand = expansion(mult = c(0, 0.05))) +