serofoi 0.1.0 New features Data simulation functions from time-varying or age-varying force of infection trends. The following is an example to simulate from a constant (in time) force of infection: foi_sim_constant <- rep(0.02, 50) serodata_constant <- generate_sim_data( sim_data = data.frame( age=seq(1,50), tsur=2050), foi=foi_sim_constant, sample_size_by_age = 5 ) To generate grouped serosurveys the function group_sim_data can be used: serodata_constant <- group_sim_data(serodata_constant , step = 5) Breaking changes Simplifies fit_seromodel output Before, the output of fit_seromodel was a list: seromodel_object <- list( fit = fit, seromodel_fit = seromodel_fit, serodata = serodata, serodata = serodata, stan_data = stan_data, ... ) Now, the output is a stan_fit object as obtained from rstan::sampling. Because of this, some plotting functionalities now require serodata as an input. Initial prior distribution parameters foi_location and foi_scale can be specified explicitely in fit_seromodel: seromodel <- fit_seromodel( serodata, foi_model = "tv_normal", foi_location = 0, foi_scale = 1 ) Depending on the selected model foi_model, the meaning of the parameters change. For the tv_normal_log model these parameters must be in logarithmic scale; the recommended usage is: seromodel <- fit_seromodel( serodata, foi_model = "tv_normal_log", foi_location = -6, foi_scale = 4 ) Chunks structure specification is now possible Before, the models estimated one value of the force of infection per year in the time spanned by the serosurvey: data(chagas2012) serodata <- prepare_serodata(chagas2012) seromodel <- fit_seromodel(serodata, foi_model = "tv_normal") Now, the amount of force of infection values estimated by the models depend on the specified chunk structure. This can either be specified by size: seromodel <- fit_seromodel(serodata, foi_model = "tv_normal", chunk_size = 10) or explicitly: chunks <- rep(c(1, 2, 3, 4, 5), c(10, 10, 15, 15, max(serodata$age_mean_f)-50)) seromodel <- fit_seromodel(serodata, foi_model = "tv_normal", chunks = chunks) Deprecate run_seromodel. Initially this function was intended to be a handler for fit_seromodel for cases when the user may need to implement the same model to multiple independent serosurveys; now we plan to showcase examples of this using the current functionalities of the package (to be added in future versions to the vignettes). Minor changes Refactorization of the visualization module plot_seroprev allows for data binning (age group manipulation) by means of parameters bin_data=TRUE and bin_step. Automatic selection of ymin and ymax aesthetics plotting functions (with the exception of plot_rhats). Correct input validation Remove duplicated data in veev2012 dataset Internal changes Remove large files from git history (see #77). Added input validation for the following functions: prepare_serodata generate_sim_data get_age_group fit_seromodel extract_seromodel_summary plot_seroprev plot_seroprev_fitted plot_foi plot_seromodel Unit testing: Separate modelling testings by model Use of dplyr::near to test models statistical validity Add tests for data simulation functions Update package template in accordance to {packagetemplate}