make all priors consistent with previous versions

epiforecasts · Dec 6, 2024 · 617ed24 · 617ed24
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commit 617ed24
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Showing 11 changed files with 12 additions and 12 deletions.
diff --git a/R/epinow.R b/R/epinow.R
@@ -65,7 +65,7 @@
 #' out <- epinow(
 #'   data = reported_cases,
 #'   generation_time = gt_opts(generation_time),
-#'   rt = rt_opts(prior = Normal(mean = 2, sd = 0.1)),
+#'   rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.1)),
 #'   delays = delay_opts(incubation_period + reporting_delay)
 #' )
 #' # summary of the latest estimates

diff --git a/R/estimate_infections.R b/R/estimate_infections.R
@@ -107,7 +107,7 @@
 #' def <- estimate_infections(reported_cases,
 #'   generation_time = gt_opts(generation_time),
 #'   delays = delay_opts(incubation_period + reporting_delay),
-#'   rt = rt_opts(prior = Normal(mean = 2, sd = 0.1))
+#'   rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.1))
 #' )
 #' # real time estimates
 #' summary(def)

diff --git a/R/opts.R b/R/opts.R
@@ -340,7 +340,7 @@ trunc_opts <- function(dist = Fixed(0), default_cdf_cutoff = 0.001,
 #' rt_opts()
 #'
 #' # add a custom length scale
-#' rt_opts(prior = Normal(mean = 2, sd = 1))
+#' rt_opts(prior = LogNormal(mean = 2, sd = 1))
 #'
 #' # add a weekly random walk
 #' rt_opts(rw = 7)

diff --git a/inst/dev/benchmark-functions.R b/inst/dev/benchmark-functions.R
@@ -17,7 +17,7 @@ create_profiles <- function(dir = file.path("inst", "stan"),
       data = reported_cases,
       generation_time = gt_opts(fixed_generation_time),
       delays = delay_opts(delays),
-      rt = rt_opts(prior = Normal(mean = 2, sd = 0.2)),
+      rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.2)),
       stan = stan_opts(
         samples = 1000, chains = 2, object = compiled_model,
         cores = 2

diff --git a/man/epinow.Rd b/man/epinow.Rd
diff --git a/man/estimate_infections.Rd b/man/estimate_infections.Rd
diff --git a/man/rt_opts.Rd b/man/rt_opts.Rd
diff --git a/tests/testthat/test-rt_opts.R b/tests/testthat/test-rt_opts.R
@@ -13,7 +13,7 @@ test_that("rt_opts returns expected default values", {
 
 test_that("rt_opts handles custom inputs correctly", {
   result <- suppressWarnings(rt_opts(
-    prior = Normal(mean = 2, sd = 0.5),
+    prior = LogNormal(mean = 2, sd = 0.5),
     use_rt = FALSE,
     rw = 7,
     use_breakpoints = FALSE,

diff --git a/vignettes/EpiNow2.Rmd.orig b/vignettes/EpiNow2.Rmd.orig
@@ -94,7 +94,7 @@ estimates <- epinow(
   data = reported_cases,
   generation_time = gt_opts(example_generation_time),
   delays = delay_opts(example_incubation_period + reporting_delay),
-  rt = rt_opts(prior = Normal(mean = 2, sd = 0.2)),
+  rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.2)),
   stan = stan_opts(cores = 4, control = list(adapt_delta = 0.99)),
   verbose = interactive()
 )
@@ -148,7 +148,7 @@ estimates <- regional_epinow(
   data = reported_cases,
   generation_time = gt_opts(example_generation_time),
   delays = delay_opts(example_incubation_period + reporting_delay),
-  rt = rt_opts(prior = Normal(mean = 2, sd = 0.2), rw = 7),
+  rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.2), rw = 7),
   gp = NULL,
   stan = stan_opts(cores = 4, warmup = 250, samples = 1000)
 )

diff --git a/vignettes/epinow.Rmd.orig b/vignettes/epinow.Rmd.orig
@@ -40,7 +40,7 @@ options(mc.cores = 4)
 reported_cases <- example_confirmed[1:60]
 reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10)
 delay <- example_incubation_period + reporting_delay
-rt_prior <- Normal(mean = 2, sd = 0.1)
+rt_prior <- LogNormal(mean = 2, sd = 0.1)
 ```
 
 We can then run the `epinow()` function with the same arguments as `estimate_infections()`.

diff --git a/vignettes/estimate_infections_options.Rmd.orig b/vignettes/estimate_infections_options.Rmd.orig
@@ -97,7 +97,7 @@ example_generation_time
 Lastly we need to choose a prior for the initial value of the reproduction number. This is assumed by the model to be normally distributed and we can set the mean and the standard deviation. We decide to set the mean to 2 and the standard deviation to 1.
 
 ```{r initial_r}
-rt_prior <- Normal(mean = 2, sd = 0.1)
+rt_prior <- LogNormal(mean = 2, sd = 0.1)
 ```
 
 # Running the model