Updates from spell_check

R/calc_independent_action.R

@@ -5,7 +5,7 @@
 #' concentration-response curves.
 #'
 #' @param conc concentrations in regular space
-#' @param max maximal (asymtotic) responses
+#' @param max maximal (asymptotic) responses
 #' @param AC50 concentrations of half-maximal response
 #' @param Emax maximum mixture response
 #' @param n Hill coefficients (slopes)

R/get_fixed_age.R

@@ -1,10 +1,10 @@
-#' Get C_ss Data for Fixed Age
+#' Get `C_ss` Data for Fixed Age
 #'
-#' @param simulated_css list of pre-generated C_ss data, for details see:
+#' @param simulated_css list of pre-generated `C_ss` data, for details see:
 #' \code{vignette("package_data", package = "GeoTox")}.
 #' @param age list of atomic vectors containing ages.
 #'
-#' @return list of matrices containing median C_ss values.
+#' @return list of matrices containing median `C_ss` values.
 #' @export
 #' 
 #' @examples

R/get_fixed_css.R

@@ -1,15 +1,15 @@
-#' Get Fixed C_ss Data
+#' Get Fixed `C_ss` Data
 #' 
 #' @description
-#' Get C_ss values for use in [sensitivity_analysis] and [compute_sensitivity].
+#' Get `C_ss` values for use in [sensitivity_analysis] and [compute_sensitivity].
 #'
-#' @param simulated_css list of pre-generated C_ss data, for details see:
+#' @param simulated_css list of pre-generated `C_ss` data, for details see:
 #' \code{vignette("package_data", package = "GeoTox")}.
 #' @param age list of atomic vectors containing ages.
 #' @param obesity list of atomic vectors containing obesity status.
-#' @param C_ss list of matrices containing C_ss values.
+#' @param C_ss list of matrices containing `C_ss` values.
 #'
-#' @return list of matrices or atomic vectors containing C_ss values.
+#' @return list of matrices or atomic vectors containing `C_ss` values.
 #' @export
 #' 
 #' @examples

R/get_fixed_obesity.R

@@ -1,10 +1,10 @@
-#' Get C_ss Data for Fixed Obesity Status
+#' Get `C_ss` Data for Fixed Obesity Status
 #'
-#' @param simulated_css list of pre-generated C_ss data, for details see:
+#' @param simulated_css list of pre-generated `C_ss` data, for details see:
 #' \code{vignette("package_data", package = "GeoTox")}.
 #' @param obesity list of atomic vectors containing obesity status.
 #'
-#' @return list of matrices containing median C_ss values.
+#' @return list of matrices containing median `C_ss` values.
 #' @export
 #' 
 #' @examples

R/get_fixed_other.R

@@ -1,8 +1,8 @@
-#' Get median C_ss Values
+#' Get median `C_ss` Values
 #'
-#' @param C_ss list of matrices containing C_ss data
+#' @param C_ss list of matrices containing `C_ss` data
 #'
-#' @return list of atomic vectors containing median C_ss values.
+#' @return list of atomic vectors containing median `C_ss` values.
 #' @export
 #' 
 #' @examples

R/get_fixed_params.R

@@ -1,10 +1,10 @@
-#' Get C_ss Data for Fixed C_ss Generation Parameters
+#' Get `C_ss` Data for Fixed `C_ss` Generation Parameters
 #'
-#' @param simulated_css list of pre-generated C_ss data, for details see:
+#' @param simulated_css list of pre-generated `C_ss` data, for details see:
 #' \code{vignette("package_data", package = "GeoTox")}.
 #' @param age list of atomic vectors containing ages.
 #'
-#' @return list of matrices containing C_ss values.
+#' @return list of matrices containing `C_ss` values.
 #' @export
 #' 
 #' @examples

R/hill_conc.R

@@ -4,7 +4,7 @@
 #' Calculate the concentration in regular space for a given response value.
 #'
 #' @param resp response value
-#' @param max maximal (asymtotic) response
+#' @param max maximal (asymptotic) response
 #' @param AC50 concentration of half-maximal response
 #' @param n Hill coefficient (slope)
 #'

R/hill_val.R

@@ -4,7 +4,7 @@
 #' Calculate the response for a given concentration in regular space.
 #'
 #' @param conc concentration in regular space
-#' @param max maximal (asymtotic) response
+#' @param max maximal (asymptotic) response
 #' @param AC50 concentration of half-maximal response
 #' @param n Hill coefficient (slope)
 #'

R/sample_Css.R

@@ -1,11 +1,11 @@
-#' Sample from pre-generated C_ss data
+#' Sample from pre-generated `C_ss` data
 #'
-#' @param simulated_css list of pre-generated C_ss data, for details see:
+#' @param simulated_css list of pre-generated `C_ss` data, for details see:
 #' \code{vignette("package_data", package = "GeoTox")}.
 #' @param age list or atomic vector of ages.
 #' @param obesity list or atomic vector of obesity status.
 #'
-#' @return list of matrices containing C_ss values. Columns are sorted to have
+#' @return list of matrices containing `C_ss` values. Columns are sorted to have
 #' consistent order across functions.
 #' 
 #' @examples

README.Rmd

@@ -47,7 +47,7 @@ pak::pak("NIEHS/GeoTox")
 
 ## Overview
 
-Figure 1 below shows the steps in the source-to-outcome-continuum or GeoTox modelling framework that is capable in the `GeoTox` package. <span style="color: blue;">blue text</span> nodes represent an object and <span style="color: green;">green text</span>, rounded nodes represent a methodology or function required to go from one to the next. The `GeoTox` package uses R S3 object-oriented programming to create the **GeoTox** object. The **GeoTox** object is a list that contains all of the information required to run the analysis including tracking exposure, assays, dose-response, and geospatial referencing. 
+Figure 1 below shows the steps in the source-to-outcome-continuum or GeoTox modeling framework that is capable in the `GeoTox` package. <span style="color: blue;">blue text</span> nodes represent an object and <span style="color: green;">green text</span>, rounded nodes represent a methodology or function required to go from one to the next. The `GeoTox` package uses R S3 object-oriented programming to create the **GeoTox** object. The **GeoTox** object is a list that contains all of the information required to run the analysis including tracking exposure, assays, dose-response, and geospatial referencing. 
 
 <p align="center">
   <img src="man/figures/GeoTox-Workflow.png" alt="GeoTox-Workflow">

README.md

@@ -47,7 +47,7 @@ pak::pak("NIEHS/GeoTox")
 ## Overview
 
 Figure 1 below shows the steps in the source-to-outcome-continuum or
-GeoTox modelling framework that is capable in the `GeoTox` package.
+GeoTox modeling framework that is capable in the `GeoTox` package.
 <span style="color: blue;">blue text</span> nodes represent an object
 and <span style="color: green;">green text</span>, rounded nodes
 represent a methodology or function required to go from one to the next.

vignettes/introduction.Rmd

@@ -23,7 +23,7 @@ library(dplyr)
 n <- 250 # Sample size
 ```
 
-> **NOTE:** The sample size here is the size of the simulated population in each region. This is different than the sample size in the "package_data" vignette, which is used to generate C_ss values for each chemical at specified age and weight combinations.
+> **NOTE:** The sample size here is the size of the simulated population in each region. This is different than the sample size in the "package_data" vignette, which is used to generate `C_ss` values for each chemical at specified age and weight combinations.
 
 ## Analysis of single assay
 

vignettes/package_data.Rmd

@@ -283,9 +283,9 @@ geo_tox_data$obesity <- places |>
   select(-OBESITY_Crude95CI)
 ```
 
-## Steady-state plasma concentration (Css)
+## Steady-state plasma concentration (`C_ss`)
 
-Use `httk` to generate Css values for combinations of age group and weight status for each chemical. The generation of these values is a time-intensive step, so one approach is to generate populations of Css values initially and then sample them later.
+Use `httk` to generate `C_ss` values for combinations of age group and weight status for each chemical. The generation of these values is a time-intensive step, so one approach is to generate populations of `C_ss` values initially and then sample them later.
 
 ```{r, eval=FALSE}
 set.seed(2345)
@@ -356,7 +356,7 @@ simulate_css <- function(chem.cas, agelim_years, weight_category,
   }
 }
 
-# Simulate Css values
+# Simulate `C_ss` values
 simulated_css <- map(casn, function(chem.cas) {
   pop_demo |>
     rowwise() |>
@@ -373,7 +373,7 @@ casn_keep <- map_lgl(simulated_css, function(df) {
 })
 simulated_css <- simulated_css[casn_keep]
 
-# Get median Css values for each age_group
+# Get median `C_ss` values for each age_group
 simulated_css <- map(
   simulated_css,
   function(cas_df) {
@@ -387,7 +387,7 @@ simulated_css <- map(
   }
 )
 
-# Get median Css values for each weight
+# Get median `C_ss` values for each weight
 simulated_css <- map(
   simulated_css,
   function(cas_df) {
@@ -407,7 +407,7 @@ geo_tox_data$simulated_css <- simulated_css
 
 # Prune data
 
-Retain only those chemicals found in exposure, dose-response and Css datasets.
+Retain only those chemicals found in exposure, dose-response and `C_ss` datasets.
 
 ```{r, eval=FALSE}
 casn_keep <- names(geo_tox_data$simulated_css)