minor spelling corrections

CITATION.cff

@@ -10,7 +10,7 @@ license: MIT
 title: 'serofoi: Bayesian Estimation of the Force of Infection from Serological Data'
 version: 1.0.2
 abstract: Estimating the force of infection from time varying, age varying, or constant
-  serocatalytic models from population based seroprevalence studies using a bayesian
+  serocatalytic models from population based seroprevalence studies using a Bayesian
   framework, including data simulation functions enabling the generation of serological
   surveys based on this models. This tool also provides a flexible prior specification
   syntax for the force of infection and the seroreversion rate, as well as methods
@@ -229,7 +229,7 @@ references:
   title: Matrix
   abstract: 'Matrix: Sparse and Dense Matrix Classes and Methods'
   notes: Imports
-  url: https://Matrix.R-forge.R-project.org
+  url: https://R-forge.R-project.org/tracker/?atid=294&group_id=61
   repository: https://CRAN.R-project.org/package=Matrix
   authors:
   - family-names: Bates

DESCRIPTION

@@ -25,7 +25,7 @@ Authors@R: c(
     person("Pontificia Universidad Javeriana", role = "cph")
   )
 Description: Estimating the force of infection from time varying, age varying, or constant
-    serocatalytic models from population based seroprevalence studies using a bayesian framework,
+    serocatalytic models from population based seroprevalence studies using a Bayesian framework,
     including data simulation functions enabling the generation of serological surveys based on this
     models. This tool also provides a flexible prior specification syntax for the force of infection
     and the seroreversion rate, as well as methods to assess model convergence and comparison

inst/WORDLIST

@@ -7,6 +7,7 @@ BMJ
 Bahia
 Bajaj
 Basáñez
+Bayesian
 Binom
 CMD
 Christl
@@ -43,6 +44,7 @@ Quevedo
 RStan
 Refactorization
 Serocatalytic
+Serological
 Seroreversion
 Serosurvey
 Serosurveys
@@ -98,9 +100,11 @@ rstan
 sd
 se
 serocatalytic
+serological
 seromodel
 seropositives
 seropositivities
+seroprevalence
 seroreversion
 serosurvey
 serosurveys

vignettes/serofoi.Rmd

@@ -47,7 +47,7 @@ Current version of ***serofoi*** includes the following assumptions on the under
 * There is no impact from migration processes in the sampled population, which means the model is not suited for a situation with high levels of migration. 
 * There are no differences in the mortality rate of infected versus susceptible individuals. This may be a limitation for situations with a high infection fatality rate, such as Ebola.
 
-## The bayesian statistical framework
+## The Bayesian statistical framework
 
 To assess how well the mathematical representation of the different FoI models describes the seroprevalence data, we implement a fitting process that relies on a Bayesian framework. The priors and upper priors for each model indicate the assumed trajectory of the FoI (either constant or time-varying). serofoi provides a set of Bayesian comparison methods for the user to choose between various possible FoI models (trajectories) that best fit the seroprevalence data. For details see [An Introduction To Force-of-Infection Models](https://epiverse-trace.github.io/serofoi/articles/foi_models.html).