1.5.0 release PR

.github/workflows/R-CMD-check.yaml

@@ -60,7 +60,6 @@ jobs:
         with:
           dependencies: NA
           extra-packages: |
-            dplyr
             rmarkdown
             rcmdcheck
             cmdstanr

.github/workflows/synthetic-validation.yaml

@@ -28,8 +28,6 @@ jobs:
           install-pandoc: false
           extra-packages: |
             here
-            dplyr
-            tidyr
             scoringutils
             loo
             matrixStats

DESCRIPTION

@@ -2,7 +2,7 @@ Type: Package
 Package: EpiNow2
 Title: Estimate Real-Time Case Counts and Time-Varying
     Epidemiological Parameters
-Version: 1.4.9000
+Version: 1.5.0.9000
 Authors@R: 
     c(person(given = "Sam",
              family = "Abbott",
@@ -125,16 +125,12 @@ Imports:
 Suggests:
     cmdstanr,
     covr,
-    dplyr,
     here,
-    kableExtra,
     knitr,
-    magrittr,
     precommit,
     rmarkdown,
     spelling,
     testthat,
-    tidyr,
     usethis,
     withr
 LinkingTo: 

NAMESPACE

@@ -58,7 +58,6 @@ export(get_generation_time)
 export(get_incubation_period)
 export(get_parameters)
 export(get_pmf)
-export(get_raw_result)
 export(get_regional_results)
 export(gp_opts)
 export(growth_to_R)

NEWS.md

@@ -1,12 +1,14 @@
-# EpiNow2 1.4.9000
+# EpiNow2 (development version)
+
+# EpiNow2 1.5.0
 
 This release comes with a change of maintainer, from @seabbs to @sbfnk.
 This is to reflect who will handle the upcoming CRAN submission, but is not expected to lead to a change in workflows.
 
 ## Major changes
 
-* Delay discretisation is now based on a two-day censoring window (with uniform probability in between), based on recommendations in [Park et al, medRxiv, 2024](https://doi.org/10.1101/2024.01.12.24301247). By @sbfnk in #518 and reviewed by @jamesmbaazam.
 * The interface to generating delay distributions has been completely overhauled. Instead of calling `dist_spec()` users now specify distributions using functions that represent the available distributions, i.e. `LogNormal()`, `Gamma()` and `Fixed()`. See `?EpiNow2::Distributions`. Uncertainty is specified using calls of the same nature, to `Normal()`. More information on the underlying design can be found in `inst/dev/design_dist.md` By @sbfnk in #504 and reviewed by @seabbs.
+* Delay discretisation is now based on a two-day censoring window (with uniform probability in between), based on recommendations in [Park et al, medRxiv, 2024](https://doi.org/10.1101/2024.01.12.24301247). By @sbfnk in #518 and reviewed by @jamesmbaazam.
 
 ## Deprecations
 

R/checks.R

@@ -3,7 +3,7 @@
 #' @description `r lifecycle::badge("stable")`
 #' `check_reports_valid()` checks that the supplied data is a `<data.frame>`,
 #' and that it has the right column names and types. In particular, it checks
-#' that the date column is in date format and does not contain NA's, and that
+#' that the date column is in date format and does not contain NAs, and that
 #' the other columns are numeric.
 #'
 #' @param data A data frame with either:

R/data.R

@@ -52,7 +52,7 @@
 #' An example dataset of observed cases with truncation applied.
 #' This data is generated internally for use in the example of
 #' `estimate_truncation()`. For details on how the data is generated, see
-#' <https://github.com/epiforecasts/EpiNow2/blob/main/data-raw/estimate-truncation.R> #nolint
+#' <https://github.com/epiforecasts/EpiNow2/blob/main/data-raw/truncated.R> #nolint
 #' @format A list of `data.table`s containing cases reported on each date until
 #' a point of truncation.
 #' Each element of the list is a `data.table` with the following columns:

R/estimate_truncation.R

@@ -4,7 +4,7 @@
 #' Estimates a truncation distribution from multiple snapshots of the same
 #' data source over time. This distribution can then be used passed to the
 #' `truncation` argument in [regional_epinow()], [epinow()], and
-#' [estimate_infections()] to adjust for truncated data and propagage the
+#' [estimate_infections()] to adjust for truncated data and propagate the
 #' uncertainty associated with data truncation into the estimates.
 #'
 #' See [here](https://gist.github.com/seabbs/176b0c7f83eab1a7192a25b28bbd116a)
@@ -79,6 +79,7 @@
 #' @importFrom checkmate assert_character assert_numeric assert_class
 #' assert_logical
 #' @examples
+#' \donttest{
 #' # set number of cores to use
 #' old_opts <- options()
 #' options(mc.cores = ifelse(interactive(), 4, 1))
@@ -109,6 +110,7 @@
 #' )
 #' plot(out)
 #' options(old_opts)
+#' }
 estimate_truncation <- function(data, max_truncation, trunc_max = 10,
                                 trunc_dist = "lognormal",
                                 truncation = trunc_opts(

R/extract.R

@@ -55,8 +55,8 @@ extract_static_parameter <- function(param, samples) {
 
 #' Extract all samples from a stan fit
 #'
-#' If the `object` argument is a <stanfit> object, it simply returns the result
-#' of [rstan::extract()]. If it is a `<CmdStanMCMC>` it returns samples
+#' If the `object` argument is a `<stanfit>` object, it simply returns the
+#' result of [rstan::extract()]. If it is a `<CmdStanMCMC>` it returns samples
 #' in the same format as [rstan::extract()] does for `<stanfit>` objects.
 #' @param stan_fit A `<stanfit>` or `<CmdStanMCMC>` object as returned by
 #'   [fit_model()].

R/stan.R

@@ -39,6 +39,7 @@ epinow2_cmdstan_model <- function(model = "estimate_infections",
   model <- monitor(cmdstanr::cmdstan_model(
     model_file,
     include_paths = dir,
+    dir = tempdir(),
     ...
   ))
   return(model)

README.Rmd

@@ -35,11 +35,11 @@ Uncertainty is propagated from all inputs into the final parameter estimates, he
 
 `{EpiNow2}` provides three models:
 
-* [`estimate_infections()`](reference/estimate_infections.html): Reconstruct cases by date of infection from reported cases.
+* `estimate_infections()`: Reconstruct cases by date of infection from reported cases.
 
-* [`estimate_secondary()`](reference/estimate_secondary.html): Estimate the relationship between primary and secondary observations, for example, deaths (secondary) based on hospital admissions (primary), or bed occupancy (secondary) based on hospital admissions (primary).
+* `estimate_secondary()`: Estimate the relationship between primary and secondary observations, for example, deaths (secondary) based on hospital admissions (primary), or bed occupancy (secondary) based on hospital admissions (primary).
 
-* [`estimate_truncation()`](reference/estimate_truncation.html): Estimate a truncation distribution from multiple snapshots of the same data source over time. For more flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package.
+* `estimate_truncation()`: Estimate a truncation distribution from multiple snapshots of the same data source over time. For more flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package.
 
 
 The default model in `estimate_infections()` uses a non-stationary Gaussian process to estimate the time-varying reproduction number and infer infections. Other options, which generally reduce runtimes at the cost of the granularity of estimates or real-time performance, include:
@@ -52,17 +52,17 @@ The default model in `estimate_infections()` uses a non-stationary Gaussian proc
 * A deconvolution/back-calculation method for inferring infections, followed with calculating the time-varying reproduction number.
 * Adjustment for the remaining susceptible population beyond the forecast horizon.
 
-The documentation for [`estimate_infections`](reference/estimate_infections.html) provides examples of the implementation of the different options available. 
+The documentation for `estimate_infections` provides examples of the implementation of the different options available. 
 
 `{EpiNow2}` is designed to be used via a single function call to two functions:
 
-* [`epinow()`](reference/epinow.html): Estimate Rt and cases by date of infection and forecast these infections into the future.
+* `epinow()`: Estimate Rt and cases by date of infection and forecast these infections into the future.
 
-* [`regional_epinow()`](reference/regional_epinow.html): Efficiently run `epinow()` across multiple regions in an efficient manner.
+* `regional_epinow()`: Efficiently run `epinow()` across multiple regions in an efficient manner.
 
-These two functions call [`estimate_infections()`](reference/estimate_infections.html), which works to reconstruct cases by date of infection from reported cases.
+These two functions call `estimate_infections()`, which works to reconstruct cases by date of infection from reported cases.
 
-For more details on using each function see the [function documentation](reference/index.html).
+For more details on using each function corresponding function documentation.
 
 </details>
 
@@ -117,7 +117,7 @@ discusses how to summarise and visualise the results after running the models.
 
 The package has two websites: one for
 [the stable release version on CRAN](https://epiforecasts.io/EpiNow2/), and
-another for [the version in development](https://epiforecasts.io/EpiNow2/dev).
+another for [the version in development](https://epiforecasts.io/EpiNow2/dev/).
 These two provide various resources for learning about the package, including
 the function reference, details about each model (model definition), workflows
 for each model (usage), and case studies or literature of applications of

README.md

@@ -59,17 +59,17 @@ Models provided
 
 `{EpiNow2}` provides three models:
 
-- [`estimate_infections()`](reference/estimate_infections.html):
-  Reconstruct cases by date of infection from reported cases.
+- `estimate_infections()`: Reconstruct cases by date of infection from
+  reported cases.
 
-- [`estimate_secondary()`](reference/estimate_secondary.html): Estimate
-  the relationship between primary and secondary observations, for
-  example, deaths (secondary) based on hospital admissions (primary), or
-  bed occupancy (secondary) based on hospital admissions (primary).
+- `estimate_secondary()`: Estimate the relationship between primary and
+  secondary observations, for example, deaths (secondary) based on
+  hospital admissions (primary), or bed occupancy (secondary) based on
+  hospital admissions (primary).
 
-- [`estimate_truncation()`](reference/estimate_truncation.html):
-  Estimate a truncation distribution from multiple snapshots of the same
-  data source over time. For more flexibility, check out the
+- `estimate_truncation()`: Estimate a truncation distribution from
+  multiple snapshots of the same data source over time. For more
+  flexibility, check out the
   [`{epinowcast}`](https://package.epinowcast.org/) package.
 
 The default model in `estimate_infections()` uses a non-stationary
@@ -90,25 +90,23 @@ cost of the granularity of estimates or real-time performance, include:
 - Adjustment for the remaining susceptible population beyond the
   forecast horizon.
 
-The documentation for
-[`estimate_infections`](reference/estimate_infections.html) provides
-examples of the implementation of the different options available.
+The documentation for `estimate_infections` provides examples of the
+implementation of the different options available.
 
 `{EpiNow2}` is designed to be used via a single function call to two
 functions:
 
-- [`epinow()`](reference/epinow.html): Estimate Rt and cases by date of
-  infection and forecast these infections into the future.
+- `epinow()`: Estimate Rt and cases by date of infection and forecast
+  these infections into the future.
 
-- [`regional_epinow()`](reference/regional_epinow.html): Efficiently run
-  `epinow()` across multiple regions in an efficient manner.
+- `regional_epinow()`: Efficiently run `epinow()` across multiple
+  regions in an efficient manner.
 
-These two functions call
-[`estimate_infections()`](reference/estimate_infections.html), which
-works to reconstruct cases by date of infection from reported cases.
+These two functions call `estimate_infections()`, which works to
+reconstruct cases by date of infection from reported cases.
 
-For more details on using each function see the [function
-documentation](reference/index.html).
+For more details on using each function corresponding function
+documentation.
 
 </details>
 
@@ -178,7 +176,7 @@ Package website
 
 The package has two websites: one for [the stable release version on
 CRAN](https://epiforecasts.io/EpiNow2/), and another for [the version in
-development](https://epiforecasts.io/EpiNow2/dev). These two provide
+development](https://epiforecasts.io/EpiNow2/dev/). These two provide
 various resources for learning about the package, including the function
 reference, details about each model (model definition), workflows for
 each model (usage), and case studies or literature of applications of

cran-comments.md

@@ -1,4 +1,11 @@
 ## R CMD check results
 
-0 errors ✔ | 0 warnings ✔ | 0 notes ✔
+This issue is submitted by a new maintainer as mentioned in a NOTE.
 
+There is also a new NOTE because an additional repository has been specified in
+order to suggest cmdstan.  This is the same approach used in brms:
+https://cran.r-project.org/web/packages/brms/index.html
+
+# Resubmission comments
+
+Size of the tar.gz has been reduced, locally confirmed as 4.7MB.

inst/WORDLIST

@@ -4,17 +4,20 @@ CMD
 CMF
 CMMID
 COVID
+CSTE
 Centers
 CoV
 Cori
 Covid
 Dirichlet
+Discretise
 Dockerfile
 ECDC
+EpiEstim
 EpiNow
 Epinow
-Gostic
 Gruson
+HHS
 Habakuk
 Hain
 HalfNormal
@@ -40,56 +43,66 @@ Nowcasts
 ORCID
 PLoS
 PMF
-PRs
 Poisson
 Quilty
 Riutort
-Rmarkdown
 Rstan
 Rtools
 Runtimes
 SACEMA
 SARS
 Sanjat
+Susswein
+VB
 Wellcome
+ast
 backcalc
 backcalculation
+bp
 centered
+cmdstanr
 codecov
 com
 csv
 dd
 defato
+detectCores
+discretisation
+discretise
 discretised
 dist
 div
 doi
 dt
+dynamicaltruncation
 epidemia
 epiforecasts
 epinow
+epinowcast
+epiparameter
 etc
 filepath
 frac
 github
 gp
 intial
+laplace
 ldots
 lengthscale
 leq
 lineranges
 linters
-logmean
-lognorm
-logsd
+lintr
 lt
 matern
 mathcal
 mathrm
 mc
+medRxiv
 metacran
 negbin
 nolint
+nonmechanistic
 nowcast
 nowcasting
 nowcasts
@@ -99,25 +112,24 @@ pak
 parallisation
 parameterisations
 parameterised
+params
+pkgdown
+pmf
 pngs
 poisson
-progressr
-rds
 realland
-reprex
-roxygen
 rstan
 runtimes
+rw
 sd
 se
 sim
 st
 stan
 stanfit
 testland
-testthat
+th
 tibbles
-tidyverse
 timelimit
 underreporting
 varphi