CRAN check fixes

epinowcast · Jul 8, 2022 · 194862e · 194862e
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diff --git a/NEWS.md b/NEWS.md
@@ -11,7 +11,7 @@ This is a major release and contains multiple breaking changes. If needing the o
 * A new helper function `enw_delay_metadata()` has been added. This produces metadata about the delay distribution vector that may be helpful in future modelling. This prepares the way for [#4](https://github.com/epiforecasts/epinowcast/issues/4) where this data frame will be combined with the reference metadata in order to build non-parametric hazard reference and delay based models. In addition to adding this function, it has also been added to the output of `enw_preprocess_data()` in order to make the metadata readily available to end-users. See [#80](https://github.com/epiforecasts/epinowcast/pull/80) by [@seabbs](https://github.com/seabbs).
 * Two new helper functions `enw_filter_reference_dates()` and `enw_filter_report_dates()` have been added. These replace `enw_retrospective_data()` but allow users to similarly construct retrospective data. Splitting these functions out into components also allows for additional use cases that were not previously possible. Note that by definition it is assumed that a report date for a given reference date must be the equal or greater (i.e a report cannot happen before the event being reported occurs). See [#82](https://github.com/epiforecasts/epinowcast/pull/82) by [@sbfnk](https://github.com/sbfnk) and [@seabbs](https://github.com/seabbs).
 * The internal grouping variables have been refactored to reduce the chance of clashes with columns in the data frames supplied by the user. There will also be an error thrown in case of a variable clash, making preprocessing safer. See [#102](https://github.com/epiforecasts/epinowcast/pull/102) by [@adrian-lison](https://github.com/adrian-lison) and [@seabbs](https://github.com/seabbs), which solves [#99](https://github.com/epiforecasts/epinowcast/issues/99).
-* Support for preprocessing observations with missing reference dates has been added along with a new data object returned by `enw_preprocess_data()` that highlights this information to the user (alternatively can be accessed by users using `enw_missing_reference()`). In addition, these missing observations have been setup to be passed to stan in order to allow their use in modelling. This feature is in prepartion of adding full support for missing observations (see [#43](https://github.com/epiforecasts/epinowcast/issues/43)). See 
+* Support for preprocessing observations with missing reference dates has been added along with a new data object returned by `enw_preprocess_data()` that highlights this information to the user (alternatively can be accessed by users using `enw_missing_reference()`). In addition, these missing observations have been setup to be passed to stan in order to allow their use in modelling. This feature is in preparation of adding full support for missing observations (see [#43](https://github.com/epiforecasts/epinowcast/issues/43)). See 
 [#106](https://github.com/epiforecasts/epinowcast/pull/106) by [@adrian-lison](https://github.com/adrian-lison) and [@seabbs](https://github.com/seabbs).
 
 ## Model

diff --git a/R/preprocess.R b/R/preprocess.R
@@ -198,7 +198,7 @@ enw_filter_report_dates <- function(obs, latest_date, remove_days) {
 #'
 #' @param include_days if \code{earilest_date} is not given, the number
 #' of reference dates to include, ending with the latest reference
-#' date included once reporting dates have been removed. If specifed
+#' date included once reporting dates have been removed. If specified
 #' this is indexed to `latest_date` or `remove_days`.
 #'
 #' @param latest_date Date, the latest reference date to include in the
@@ -591,7 +591,7 @@ enw_delay_metadata <- function(max_delay = 20, breaks = 4) {
 #' of [enw_preprocess_data()] for more on the expected inputs.
 #'
 #' @param obs Observations with the addition of empirical reporting proportions
-#'  and and restricted to the specified maximum dela.
+#'  and and restricted to the specified maximum delay.
 #'
 #' @param new_confirm Incidence of notifications by reference and report date.
 #' Empirical reporting distributions are also added.

diff --git a/inst/WORDLIST b/inst/WORDLIST
@@ -5,6 +5,7 @@ CmdStan
 CmdStanR
 CmdStanR's
 CmdStanR’s
+Cmdstan
 Codecov
 Höhle
 ImperialCollegeLondon
@@ -13,13 +14,16 @@ Lifecycle
 LogNormal
 Nowcast
 Nowcasting
+ORCID
 PARAM
 Poisson
+Rstan
 aem
 com
 discretised
 enw
 epidemia
+fns
 formulatools
 frac
 geq
@@ -38,7 +42,6 @@ nowcast
 nowcasting
 nowcasts
 overprediction
-parallisation
 parameterisations
 postprocess
 postprocessing
@@ -52,5 +55,4 @@ startsWith
 sundays
 th
 tradeoffs
-treatss
 underprediction
diff --git a/man/enw_construct_data.Rd b/man/enw_construct_data.Rd
diff --git a/man/enw_filter_reference_dates.Rd b/man/enw_filter_reference_dates.Rd
diff --git a/tests/testthat/test-enw_missing_reference.R b/tests/testthat/test-enw_missing_reference.R
@@ -14,10 +14,10 @@ test_that("enw_missing_reference works as expected given correct input data", {
     new_confirm = c(1, rep(0, 11), 4)
   )
   exp_obs <- data.table::data.table(
-    .group = 1, location = "DE",
     report_date = as.IDate(
-      seq.Date(as.Date("2021-10-01"), as.Date("2021-10-04"), by = "day")
-    ),
+        seq.Date(as.Date("2021-10-01"), as.Date("2021-10-04"), by = "day")
+      ),
+    .group = 1, location = "DE",
     confirm = c(rep(0, 3), 4), prop_missing = c(0, NaN, NaN, 1)
   )
   expect_equal(enw_missing_reference(obs), exp_obs)