Finish updating curve_params to sr_params

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: serocalculator
 Title: Estimating Infection Rates from Serological Data
-Version: 1.3.0.9050
+Version: 1.3.0.9051
 Authors@R: c(
     person("Peter", "Teunis", , "p.teunis@emory.edu", role = c("aut", "cph"),
            comment = "Author of the method and original code."),

NEWS.md

@@ -6,7 +6,7 @@
 * Added new functions `analyze_sims()` and `autoplot.sim_results()` (#444)
 * Rename `estimate_scr()` to `est_seroincidence_by()` (#439)
 * Rename `estimate_scr()` to `est_seroincidence()` (#432)
-* Rename argument `curve_params` to `sr_params` (#424)
+* Rename argument `curve_params` to `sr_params` for estimation functions (#424)
 * added documentation for `count_strata()` (#431)
 * Rename  `as_curve_params()` to `as_sr_params()` (#421)
 * Rename `load_curve_params()` to `load_sr_params()` (#421)

R/autoplot.seroincidence.by.R

@@ -24,7 +24,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = c("catchment"),
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   curve_strata_varnames= NULL,
 #'   noise_strata_varnames = NULL,
 #'   noise_params = noise,

R/autoplot.summary.seroincidence.by.R

@@ -32,7 +32,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = c("catchment", "ageCat"),
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   noise_params = noise,
 #'   curve_strata_varnames= NULL,
 #'   noise_strata_varnames = NULL,

R/est_seroincidence_by.R

@@ -31,7 +31,7 @@
 #'
 #' @inheritParams est_seroincidence
 #' @inheritParams log_likelihood
-#' @inheritDotParams est_seroincidence -sr_params
+#' @inheritDotParams est_seroincidence
 #' @inheritDotParams stats::nlm -f -p -hessian -print.level -steptol
 #'
 #' @return
@@ -60,7 +60,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = "catchment",
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   noise_params = noise,
 #'   antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
 #'   # num_cores = 8 # Allow for parallel processing to decrease run time
@@ -71,7 +71,7 @@
 #'
 est_seroincidence_by <- function(
     pop_data,
-    curve_params,
+    sr_params,
     noise_params,
     strata,
     curve_strata_varnames = strata,
@@ -109,7 +109,7 @@ est_seroincidence_by <- function(
     to_return <-
       est_seroincidence(
         pop_data = pop_data,
-        sr_params = curve_params,
+        sr_params = sr_params,
         noise_params = noise_params,
         lambda_start = lambda_start,
         antigen_isos = antigen_isos,
@@ -125,14 +125,14 @@ est_seroincidence_by <- function(
   .errorCheck(
     data = pop_data,
     antigen_isos = antigen_isos,
-    curve_params = curve_params
+    curve_params = sr_params
   )
 
   # Split data per stratum
   stratum_data_list <- stratify_data(
     antigen_isos = antigen_isos,
     data = pop_data |> filter(.data$antigen_iso %in% antigen_isos),
-    curve_params = curve_params |> filter(.data$antigen_iso %in% antigen_isos),
+    curve_params = sr_params |> filter(.data$antigen_iso %in% antigen_isos),
     noise_params = noise_params |> filter(.data$antigen_iso %in% antigen_isos),
     strata_varnames = strata,
     curve_strata_varnames = curve_strata_varnames,

R/print.seroincidence.by.R

@@ -25,7 +25,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = c("catchment"),
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   noise_params = noise,
 #'   antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
 #'   # num_cores = 8 # Allow for parallel processing to decrease run time

R/print.summary.seroincidence.by.R

@@ -26,7 +26,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = c("catchment"),
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   noise_params = noise,
 #'   antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
 #'   # num_cores = 8 # Allow for parallel processing to decrease run time

R/summary.seroincidence.by.R

@@ -53,7 +53,7 @@
 #' est2 <- est_seroincidence_by(
 #'   strata = c("catchment"),
 #'   pop_data = xs_data,
-#'   curve_params = curve,
+#'   sr_params = curve,
 #'   noise_params = noise,
 #'   antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
 #'   # num_cores = 8 # Allow for parallel processing to decrease run time

data-raw/sees_typhoid_ests_strat.R

@@ -12,7 +12,7 @@ noise <- "https://osf.io/download//hqy4v/" |> readr::read_rds()
 sees_typhoid_ests_strat <- est_seroincidence_by(
   strata = c("ageCat", "Country"),
   pop_data = xs_data,
-  curve_params = curve,
+  sr_params = curve,
   curve_strata_varnames = NULL,
   noise_params = noise,
   noise_strata_varnames = "Country",

inst/examples/exm-analyze_sims.R

@@ -1,4 +1,4 @@
 \donttest{
 dmcmc <- typhoid_curves_nostrat_100
 
 n_cores <- 2
@@ -13,46 +13,45 @@
 antibodies <- c("HlyE_IgA", "HlyE_IgG")
 lifespan <- c(0, 10)
 dlims = rbind(
-  "HlyE_IgA" = c(min = 0, max = 0.5),
-  "HlyE_IgG" = c(min = 0, max = 0.5)
+"HlyE_IgA" = c(min = 0, max = 0.5),
+"HlyE_IgG" = c(min = 0, max = 0.5)
+)
+sim_df <- sim_pop_data_multi(
+n_cores = n_cores,
+lambdas = lambdas,
+nclus = nclus,
+sample_sizes = nrep,
+age_range = lifespan,
+antigen_isos = antibodies,
+renew_params = FALSE,
+add_noise = TRUE,
+curve_params = dmcmc,
+noise_limits = dlims,
+format = "long"
 )
-sim_df <-
-  sim_pop_data_multi(
-    n_cores = n_cores,
-    lambdas = lambdas,
-    nclus = nclus,
-    sample_sizes = nrep,
-    age_range = lifespan,
-    antigen_isos = antibodies,
-    renew_params = FALSE,
-    add_noise = TRUE,
-    curve_params = dmcmc,
-    noise_limits = dlims,
-    format = "long"
-  )
 cond <- tibble::tibble(
-  antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
-  nu = c(0.5, 0.5), # Biologic noise (nu)
-  eps = c(0, 0), # M noise (eps)
-  y.low = c(1, 1), # low cutoff (llod)
-  y.high = c(5e6, 5e6)
+antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
+nu = c(0.5, 0.5), # Biologic noise (nu)
+eps = c(0, 0), # M noise (eps)
+y.low = c(1, 1), # low cutoff (llod)
+y.high = c(5e6, 5e6)
 )
 ests <-
-  est_seroincidence_by(
-    pop_data = sim_df,
-    curve_params = dmcmc,
-    noise_params = cond,
-    num_cores = n_cores,
-    strata = c("lambda.sim", "sample_size", "cluster"),
-    curve_strata_varnames = NULL,
-    noise_strata_varnames = NULL,
-    verbose = FALSE,
-    build_graph = FALSE, # slows down the function substantially
-    antigen_isos = c("HlyE_IgG", "HlyE_IgA")
-  )
+est_seroincidence_by(
+pop_data = sim_df,
+sr_params = dmcmc,
+noise_params = cond,
+num_cores = n_cores,
+strata = c("lambda.sim", "sample_size", "cluster"),
+curve_strata_varnames = NULL,
+noise_strata_varnames = NULL,
+verbose = FALSE,
+build_graph = FALSE, # slows down the function substantially
+antigen_isos = c("HlyE_IgG", "HlyE_IgA")
+)
 
 ests |>
-  summary() |>
-  analyze_sims()
+summary() |>
+analyze_sims()
 
 }

inst/examples/exm-autoplot.sim_results.R

@@ -1,58 +1,58 @@
 \donttest{
-  dmcmc <- typhoid_curves_nostrat_100
+dmcmc <- typhoid_curves_nostrat_100
 
-  n_cores <- 2
+n_cores <- 2
 
-  nclus <- 20
-  # cross-sectional sample size
-  nrep <- c(50, 200)
+nclus <- 20
+# cross-sectional sample size
+nrep <- c(50, 200)
 
-  # incidence rate in e
-  lambdas <- c(.05, .8)
-  lifespan <- c(0, 10)
-  antibodies <- c("HlyE_IgA", "HlyE_IgG")
-  dlims <- rbind(
-    "HlyE_IgA" = c(min = 0, max = 0.5),
-    "HlyE_IgG" = c(min = 0, max = 0.5)
-  )
-  sim_df <-
-    sim_pop_data_multi(
-      n_cores = n_cores,
-      lambdas = lambdas,
-      nclus = nclus,
-      sample_sizes = nrep,
-      age_range = lifespan,
-      antigen_isos = antibodies,
-      renew_params = FALSE,
-      add_noise = TRUE,
-      curve_params = dmcmc,
-      noise_limits = dlims,
-      format = "long"
-    )
-  cond <- tibble::tibble(
-    antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
-    nu = c(0.5, 0.5), # Biologic noise (nu)
-    eps = c(0, 0), # M noise (eps)
-    y.low = c(1, 1), # low cutoff (llod)
-    y.high = c(5e6, 5e6)
-  )
-  ests <-
-    est_seroincidence_by(
-      pop_data = sim_df,
-      curve_params = dmcmc,
-      noise_params = cond,
-      num_cores = n_cores,
-      strata = c("lambda.sim", "sample_size", "cluster"),
-      curve_strata_varnames = NULL,
-      noise_strata_varnames = NULL,
-      verbose = FALSE,
-      build_graph = FALSE, # slows down the function substantially
-      antigen_isos = c("HlyE_IgG", "HlyE_IgA")
-    )
+# incidence rate in e
+lambdas <- c(.05, .8)
+lifespan <- c(0, 10)
+antibodies <- c("HlyE_IgA", "HlyE_IgG")
+dlims <- rbind(
+"HlyE_IgA" = c(min = 0, max = 0.5),
+"HlyE_IgG" = c(min = 0, max = 0.5)
+)
+sim_df <-
+sim_pop_data_multi(
+n_cores = n_cores,
+lambdas = lambdas,
+nclus = nclus,
+sample_sizes = nrep,
+age_range = lifespan,
+antigen_isos = antibodies,
+renew_params = FALSE,
+add_noise = TRUE,
+curve_params = dmcmc,
+noise_limits = dlims,
+format = "long"
+)
+cond <- tibble::tibble(
+antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
+nu = c(0.5, 0.5), # Biologic noise (nu)
+eps = c(0, 0), # M noise (eps)
+y.low = c(1, 1), # low cutoff (llod)
+y.high = c(5e6, 5e6)
+)
+ests <-
+est_seroincidence_by(
+pop_data = sim_df,
+sr_params = dmcmc,
+noise_params = cond,
+num_cores = n_cores,
+strata = c("lambda.sim", "sample_size", "cluster"),
+curve_strata_varnames = NULL,
+noise_strata_varnames = NULL,
+verbose = FALSE,
+build_graph = FALSE, # slows down the function substantially
+antigen_isos = c("HlyE_IgG", "HlyE_IgA")
+)
 
-  ests |>
-    summary() |>
-    analyze_sims() |>
-    autoplot()
+ests |>
+summary() |>
+analyze_sims() |>
+autoplot()
 
 }

inst/examples/exm-strat_ests_barplot.R

@@ -14,7 +14,7 @@ noise <-
 est2 <- est_seroincidence_by(
   strata = c("catchment", "ageCat"),
   pop_data = xs_data,
-  curve_params = curve,
+  sr_params = curve,
   noise_params = noise,
   curve_strata_varnames = NULL,
   noise_strata_varnames = NULL,

inst/examples/exm-strat_ests_scatterplot.R

@@ -14,7 +14,7 @@ noise <-
 est2 <- est_seroincidence_by(
   strata = c("catchment", "ageCat"),
   pop_data = xs_data,
-  curve_params = curve,
+  sr_params = curve,
   noise_params = noise,
   curve_strata_varnames = NULL,
   noise_strata_varnames = NULL,