diff --git a/NAMESPACE b/NAMESPACE
index b632f8922..4a678f56f 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,6 +1,5 @@
 # Generated by roxygen2: do not edit by hand
 
-S3method(bake,step_epi_ahead)
 S3method(bake,step_epi_lag)
 S3method(epi_keys,default)
 S3method(epi_keys,epi_df)
@@ -8,9 +7,7 @@ S3method(epi_keys,recipe)
 S3method(epi_recipe,default)
 S3method(epi_recipe,epi_df)
 S3method(epi_recipe,formula)
-S3method(prep,step_epi_ahead)
 S3method(prep,step_epi_lag)
-S3method(print,step_epi_ahead)
 S3method(print,step_epi_lag)
 export("%>%")
 export(arx_args_list)
@@ -27,7 +24,6 @@ export(knnarx_args_list)
 export(knnarx_forecaster)
 export(smooth_arx_args_list)
 export(smooth_arx_forecaster)
-export(step_epi_ahead)
 export(step_epi_lag)
 import(recipes)
 importFrom(magrittr,"%>%")
diff --git a/R/epi_ahead.R b/R/epi_ahead.R
deleted file mode 100644
index 3434b7d93..000000000
--- a/R/epi_ahead.R
+++ /dev/null
@@ -1,163 +0,0 @@
-#' Create a leading outcome
-#'
-#' `step_epi_ahead` creates a *specification* of a recipe step that
-#'   will add new columns of leading data. Leading data will
-#'   by default include NA values where the lag was induced.
-#'   These can be removed with [step_naomit()], or you may
-#'   specify an alternative filler value with the `default`
-#'   argument.
-#'
-#' @param recipe A recipe object. The step will be added to the
-#'  sequence of operations for this recipe.
-#' @param ... One or more selector functions to choose variables
-#'  for this step. See [selections()] for more details.
-#' @param role For model terms created by this step, what analysis role should
-#'  they be assigned?
-#' @param trained A logical to indicate if the quantities for
-#'  preprocessing have been estimated.
-#' @param ahead A vector of positive integers. Each specified column will be
-#'  lead for each value in the vector.
-#' @param prefix A prefix for generated column names, default to "ahead_".
-#' @param default Determines what fills empty rows
-#'   left by leading/lagging (defaults to NA).
-#' @param keys A character vector of the keys in an epi_df
-#' @param columns A character string of variable names that will
-#'  be populated (eventually) by the `terms` argument.
-#' @param skip A logical. Should the step be skipped when the
-#'  recipe is baked by [bake()]? While all operations are baked
-#'  when [prep()] is run, some operations may not be able to be
-#'  conducted on new data (e.g. processing the outcome variable(s)).
-#'  Care should be taken when using `skip = TRUE` as it may affect
-#'  the computations for subsequent operations.
-#' @param id A character string that is unique to this step to identify it.
-#' @template step-return
-#'
-#' @details The step assumes that the data are already _in the proper sequential
-#'  order_ for leading.
-#'
-#' @family row operation steps
-#' @export
-#'
-#' @examples
-#' tib <- tibble::tibble(
-#'   x = 1:5, y = 1:5,
-#'   time_value = seq(as.Date("2020-01-01"), by = 1, length.out = 5),
-#'   geo_value = "ca"
-#'   ) %>% epiprocess::as_epi_df()
-#'
-#' library(recipes)
-#' epi_recipe(y ~ x, data = tib) %>%
-#'   step_epi_lag(x, lag = 2:3) %>%
-#'   step_epi_ahead(y, ahead = 1) %>%
-#'   prep(tib) %>%
-#'   bake(tib)
-step_epi_ahead <-
-  function(recipe,
-           ...,
-           role = "outcome",
-           trained = FALSE,
-           ahead = 1,
-           prefix = "ahead_",
-           default = NA,
-           keys = epi_keys(recipe),
-           columns = NULL,
-           skip = FALSE,
-           id = rand_id("epi_ahead")) {
-    add_step(
-      recipe,
-      step_epi_ahead_new(
-        terms = dplyr::enquos(...),
-        role = role,
-        trained = trained,
-        ahead = ahead,
-        prefix = prefix,
-        default = default,
-        keys = keys,
-        columns = columns,
-        skip = skip,
-        id = id
-      )
-    )
-  }
-
-step_epi_ahead_new <-
-  function(terms, role, trained, ahead, prefix, default, keys,
-           columns, skip, id) {
-    step(
-      subclass = "epi_ahead",
-      terms = terms,
-      role = role,
-      trained = trained,
-      ahead = ahead,
-      prefix = prefix,
-      default = default,
-      keys = keys,
-      columns = columns,
-      skip = skip,
-      id = id
-    )
-  }
-
-#' @export
-prep.step_epi_ahead <- function(x, training, info = NULL, ...) {
-  step_epi_ahead_new(
-    terms = x$terms,
-    role = x$role,
-    trained = TRUE,
-    ahead = x$ahead,
-    prefix = x$prefix,
-    default = x$default,
-    keys = x$keys,
-    columns = recipes_eval_select(x$terms, training, info),
-    skip = x$skip,
-    id = x$id
-  )
-}
-
-#' @export
-bake.step_epi_ahead <- function(object, new_data, ...) {
-  if (!all(object$ahead == as.integer(object$ahead))) {
-    rlang::abort("step_epi_ahead requires 'ahead' argument to be integer valued.")
-  }
-
-  grid <- tidyr::expand_grid(
-    col = object$columns, lag_val = -object$ahead) %>%
-    dplyr::mutate(
-      ahead_val = -lag_val,
-      newname = glue::glue("{object$prefix}{ahead_val}_{col}")
-    ) %>%
-    dplyr::select(-ahead_val)
-
-  ## ensure no name clashes
-  new_data_names <- colnames(new_data)
-  intersection <- new_data_names %in% grid$newname
-  if (any(intersection)) {
-    rlang::abort(
-      paste0("Name collision occured in `", class(object)[1],
-             "`. The following variable names already exists: ",
-             paste0(new_data_names[intersection], collapse = ", "),
-             "."))
-  }
-
-  ok <- object$keys
-  lagged <- purrr::reduce(
-    purrr::pmap(grid, epi_shift_single, x = new_data, key_cols = ok),
-    dplyr::full_join,
-    by = ok
-  )
-
-  dplyr::full_join(new_data, lagged, by = ok) %>%
-    dplyr::group_by(dplyr::across(dplyr::all_of(ok[-1]))) %>%
-    dplyr::arrange(time_value) %>%
-    dplyr::ungroup()
-
-}
-
-#' @export
-print.step_epi_ahead <-
-  function(x, width = max(20, options()$width - 30), ...) {
-    ## TODO add printing of the lags
-    title <- "Leading "
-    recipes::print_step(x$columns, x$terms, x$trained, title, width)
-    invisible(x)
-  }
diff --git a/R/epi_lag.R b/R/epi_lag.R
index b7dc28b2a..46c93f105 100644
--- a/R/epi_lag.R
+++ b/R/epi_lag.R
@@ -16,13 +16,13 @@
 #'
 #' @family row operation steps
 #' @export
-#' @rdname step_epi_ahead
+#' @rdname step_epi_lag
 step_epi_lag <-
   function(recipe,
            ...,
            role = "predictor",
            trained = FALSE,
-           lag = 1,
+           lag = 1, # negative for ahead
            prefix = "lag_",
            default = NA,
            keys = epi_keys(recipe),
@@ -117,7 +117,7 @@ bake.step_epi_lag <- function(object, new_data, ...) {
 print.step_epi_lag <-
   function(x, width = max(20, options()$width - 30), ...) {
     ## TODO add printing of the lags
-    title <- "Lagging "
+    title <- ifelse(x$lag >= 0, "Lagging", "Leading")
     recipes::print_step(x$columns, x$terms, x$trained, title, width)
     invisible(x)
   }
diff --git a/man/step_epi_ahead.Rd b/man/step_epi_ahead.Rd
deleted file mode 100644
index 006c224c3..000000000
--- a/man/step_epi_ahead.Rd
+++ /dev/null
@@ -1,117 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/epi_ahead.R, R/epi_lag.R
-\name{step_epi_ahead}
-\alias{step_epi_ahead}
-\alias{step_epi_lag}
-\title{Create a leading outcome}
-\usage{
-step_epi_ahead(
-  recipe,
-  ...,
-  role = "outcome",
-  trained = FALSE,
-  ahead = 1,
-  prefix = "ahead_",
-  default = NA,
-  keys = epi_keys(recipe),
-  columns = NULL,
-  skip = FALSE,
-  id = rand_id("epi_ahead")
-)
-
-step_epi_lag(
-  recipe,
-  ...,
-  role = "predictor",
-  trained = FALSE,
-  lag = 1,
-  prefix = "lag_",
-  default = NA,
-  keys = epi_keys(recipe),
-  columns = NULL,
-  skip = FALSE,
-  id = rand_id("epi_lag")
-)
-}
-\arguments{
-\item{recipe}{A recipe object. The step will be added to the
-sequence of operations for this recipe.}
-
-\item{...}{One or more selector functions to choose variables
-for this step. See \code{\link[=selections]{selections()}} for more details.}
-
-\item{role}{For model terms created by this step, what analysis role should
-they be assigned?}
-
-\item{trained}{A logical to indicate if the quantities for
-preprocessing have been estimated.}
-
-\item{ahead}{A vector of positive integers. Each specified column will be
-lead for each value in the vector.}
-
-\item{prefix}{A prefix for generated column names, default to "ahead_".}
-
-\item{default}{Determines what fills empty rows
-left by leading/lagging (defaults to NA).}
-
-\item{keys}{A character vector of the keys in an epi_df}
-
-\item{columns}{A character string of variable names that will
-be populated (eventually) by the \code{terms} argument.}
-
-\item{skip}{A logical. Should the step be skipped when the
-recipe is baked by \code{\link[=bake]{bake()}}? While all operations are baked
-when \code{\link[=prep]{prep()}} is run, some operations may not be able to be
-conducted on new data (e.g. processing the outcome variable(s)).
-Care should be taken when using \code{skip = TRUE} as it may affect
-the computations for subsequent operations.}
-
-\item{id}{A character string that is unique to this step to identify it.}
-
-\item{lag}{A vector of positive integers. Each specified column will be
-lagged for each value in the vector.}
-}
-\value{
-An updated version of \code{recipe} with the new step added to the
-sequence of any existing operations.
-
-An updated version of \code{recipe} with the new step added to the
-sequence of any existing operations.
-}
-\description{
-\code{step_epi_ahead} creates a \emph{specification} of a recipe step that
-will add new columns of leading data. Leading data will
-by default include NA values where the lag was induced.
-These can be removed with \code{\link[=step_naomit]{step_naomit()}}, or you may
-specify an alternative filler value with the \code{default}
-argument.
-
-\code{step_epi_lag} creates a \emph{specification} of a recipe step that
-will add new columns of lagged data. Lagged data will
-by default include NA values where the lag was induced.
-These can be removed with \code{\link[=step_naomit]{step_naomit()}}, or you may
-specify an alternative filler value with the \code{default}
-argument.
-}
-\details{
-The step assumes that the data are already \emph{in the proper sequential
-order} for leading.
-
-The step assumes that the data are already \emph{in the proper sequential
-order} for lagging.
-}
-\examples{
-tib <- tibble::tibble(
-  x = 1:5, y = 1:5,
-  time_value = seq(as.Date("2020-01-01"), by = 1, length.out = 5),
-  geo_value = "ca"
-  ) \%>\% epiprocess::as_epi_df()
-
-library(recipes)
-epi_recipe(y ~ x, data = tib) \%>\%
-  step_epi_lag(x, lag = 2:3) \%>\%
-  step_epi_ahead(y, ahead = 1) \%>\%
-  prep(tib) \%>\%
-  bake(tib)
-}
-\concept{row operation steps}
diff --git a/man/step_epi_lag.Rd b/man/step_epi_lag.Rd
new file mode 100644
index 000000000..52361f696
--- /dev/null
+++ b/man/step_epi_lag.Rd
@@ -0,0 +1,41 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/epi_lag.R
+\name{step_epi_lag}
+\alias{step_epi_lag}
+\title{Create a lagged predictor}
+\usage{
+step_epi_lag(
+  recipe,
+  ...,
+  role = "predictor",
+  trained = FALSE,
+  lag = 1,
+  prefix = "lag_",
+  default = NA,
+  keys = epi_keys(recipe),
+  columns = NULL,
+  skip = FALSE,
+  id = rand_id("epi_lag")
+)
+}
+\arguments{
+\item{lag}{A vector of positive integers. Each specified column will be
+lagged for each value in the vector.}
+}
+\value{
+An updated version of \code{recipe} with the new step added to the
+sequence of any existing operations.
+}
+\description{
+\code{step_epi_lag} creates a \emph{specification} of a recipe step that
+will add new columns of lagged data. Lagged data will
+by default include NA values where the lag was induced.
+These can be removed with \code{\link[=step_naomit]{step_naomit()}}, or you may
+specify an alternative filler value with the \code{default}
+argument.
+}
+\details{
+The step assumes that the data are already \emph{in the proper sequential
+order} for lagging.
+}
+\concept{row operation steps}
diff --git a/musings/example-recipe.R b/musings/example-recipe.R
index 61e4b6868..d10bd7e8d 100644
--- a/musings/example-recipe.R
+++ b/musings/example-recipe.R
@@ -36,7 +36,7 @@ xx <- x %>% filter(time_value > "2021-12-01")
 # Baseline AR3
 r <- epi_recipe(x) %>% # if we add this as a class, maybe we get better
                        # behaviour downstream?
-  step_epi_ahead(death_rate, ahead = 7) %>%
+  step_epi_lag(death_rate, lag = -7) %>%
   step_epi_lag(death_rate, lag = c(0, 7, 14)) %>%
   step_epi_lag(case_rate, lag = c(0, 7, 14)) %>%
   step_naomit(all_predictors()) %>%
diff --git a/tests/testthat/test-assign_arg_list.R b/tests/testthat/test-assign_arg_list.R
new file mode 100644
index 000000000..017c40935
--- /dev/null
+++ b/tests/testthat/test-assign_arg_list.R
@@ -0,0 +1,6 @@
+test_that("First argument must be a list",{
+  expect_error(assign_arg_list(c(1,2,3)))
+})
+test_that("All arguments should be named",{
+  expect_error(assign_arg_list(list(1,2)))
+})
diff --git a/tests/testthat/test-df_mat_mul.R b/tests/testthat/test-df_mat_mul.R
new file mode 100644
index 000000000..166fdc92d
--- /dev/null
+++ b/tests/testthat/test-df_mat_mul.R
@@ -0,0 +1,19 @@
+df <- data.frame(matrix(1:100, ncol = 5))
+mat <- matrix(1:4, ncol = 2)
+df_mat_mul(df, mat, "z", dplyr::num_range("X", 2:3))
+test_that("df_mat_mul checks inputs", {
+  expect_error(df_mat_mul(30,mat))
+  expect_error(df_mat_mul(df,20))
+})
+
+test_that("Incompatible matrix multipication cannot happen", {
+  expect_error(df_mat_mul(df, mat, "z", dplyr::num_range("X", 1:3)))
+})
+
+test_that("Matrix multiplication is being handled as expected", {
+  X <- df[c(1,4,5)]
+  Z <- as.data.frame(as.matrix(df[2:3]) %*% mat)
+  colnames(Z) <- c("z1","z2")
+  output <- cbind(X,Z)
+  expect_identical(df_mat_mul(df,mat, "z", dplyr::num_range("X", 2:3)),output)
+})