Package index • naomi

All functions
`Imports`	We need to import these as they are used by dependencies (first90) unalified and need to be available in the package environment for the tests to be able to run in a background progress (i.e. when running in parllel)
`add_output_labels()`	Add labels to output indicators
`age_bar_plotly()`	Plotly barplot comparing age distribution of survey inputs and naomi outputs
`aggregate_anc()`	Aggregate ANC data according to area hierarchy
`aggregate_art()`	Aggregate ART data according to area hierarchy
`align_inputs_outputs()`	Align model data inputs and model estimates
`anc_testing_prev_mf()` `anc_testing_artcov_mf()` `anc_testing_clients_mf()`	Prepare Model Frames for Programme Datasets
`artnum_mf()`	Build artnum model frame
`assert_pjnz_shiny90()`	Check whether PJNZ contains .shiny90 file
`bar_plotly()`	Plotly barplot comparing geographical distribution of data inputs and naomi outputs
`build_hierarchy_label()`	Return the translated label & description for a set of plot types
`calculate_prevalence_art_coverage()`	Calculate prevalence and ART coverage from ANC input data
`calibrate_outputs()`	Calibrate naomi model outputs
`cmc_date()`	Convert Date to Century Month Code (CMC)
`create_adj_matrix()`	Create adjacency matrix from spatial polygons
`create_area_aggregation()`	Long data frame mapping area hierarchy areas to model level areas
`create_areas()`	Create an Areas Object
`create_edge_list()`	Create edgelist from adjacency matrix
`cut_naomi_age_group()`	Cut Five Year Age Groups
`data_type_labels()`	Get id to label mapping for calibration plot data type
`demo_anc_testing` `demo_art_number`	Programme data: Malawi routine HIV service delivery data
`demo_area_boundaries`	Malawi area boundaries.
`demo_area_hierarchy`	Malawi area hierarchy
`demo_area_levels`	Malawi area levels.
`demo_population_agesex`	Malawi age-sex stratified population data
`demo_survey_biomarker`	Malawi survye biomarkers
`demo_survey_clusters`	Malawi survey clusters
`demo_survey_hiv_indicators`	Malawi HIV indicators
`demo_survey_individuals`	Malawi survey individuals
`demo_survey_meta`	Malawi survey metadata
`demo_survey_regions`	Malawi survey regions
`disaggregate_0to4_outputs()`	Disaggregate age 0-4 outputs to <1 / 1-4
`district_barplot()`	Create district bar plot
`dropdown_buttons()`	Automatically make drop drop buttons for plotly filter
`extract_pjnz_naomi()`	Extract Model Inputs from Spectrum PJNZ
`extract_pjnz_program_data()`	Extract ART and ANC testing program data inputs from Spectrum PJNZ
`extract_shiny90_age_sex()`	Export proportion aware by five year age group from Shiny90
`fit_tmb()`	Fit TMB model
`get_age_groups()`	Data frame of age groups
`get_anc_metadata()`	Metadata for ANC plot types used in the input time series plots. Mainly for internal use.
`get_area_collection()`	Get a collection of areas
`get_art_metadata()`	Metadata for ART plot types used in the input time series plots. Mainly for internal use.
`get_five_year_age_groups()`	Get 5 year age groups
`get_meta_indicator()`	Get indicator metadata
`get_metadata()`	Get indicator metadata as a data frame
`get_plot_type_column_metadata()`	Return the translated label & description for a set of plot types
`get_plotting_metadata()`	Get plotting metadata for a particular country
`get_spec_aggr_interpolation()`	Interpolate Spectrum to quarter_id
`hintr_calibrate()`	Calibrate hintr_output
`hintr_calibrate_plot()`	Get data for hintr calibrate plot
`hintr_comparison_plot()`	Get data for hintr comparison plot
`hintr_prepare_agyw_download()`	Prepare AGYW tool download
`hintr_prepare_coarse_age_group_download()`	Prepare coarse age group download
`hintr_prepare_comparison_report_download()`	Prepare comparison report download
`hintr_prepare_datapack_download()`	Prepare Datapack download
`hintr_prepare_spectrum_download()`	Prepare spectrum download
`hintr_prepare_summary_report_download()`	Prepare summary report download
`hintr_run_model()`	Run the model and save output
`hintr_validate_anc_programme_data()`	Run validation for subnational programme data input
`hintr_validate_art_programme_data()`	Run validation for subnational programme data input
`interpolate_population_agesex()`	Log-linear interpolation of age/sex stratified population
`log_linear_interp()`	Log-linear interpolation of NA values
`map_outputs()`	Create output map plot
`naomi_model_frame()`	Construct Model Frames and Adjacency Structures
`naomi_objective_function_r()`	R implementation of Naomi model
`naomi_output_frame()`	Model Frame and Linear Transform for Aggregated Model Outputs
`output_naomi_warning()`	Generate naomi warning for specific strata of simulated outputs
`output_package()`	Build output package from fit
`pop_pyramid_outputs()`	Create population pyramid plot
`prepare_input_time_series_anc()`	Prepare data for ANC input time series plots
`prepare_input_time_series_art()`	Prepare data for ART input time series plots
`prepare_spectrum_naomi_comparison()`	Compare aggregated subnational Naomi + spectrum totals for comparison table
`prepare_tmb_inputs()`	Prepare inputs for TMB model.
`quarter_year_labels()` `quarter_number()` `quarter_labels()` `calendar_quarter_labels()` `calendar_quarter_labels_short()` `year_labels()` `convert_quarter_id()` `convert_calendar_quarter()` `calendar_quarter_to_quarter_id()` `quarter_id_to_calendar_quarter()` `calendar_quarter_to_year()` `calendar_quarter_to_quarter()`	Time period indexing
`read_hintr_output()`	Read hintr output
`read_population()` `read_survey_indicators()` `read_art_number()` `read_anc_testing()` `read_area_merged()`	Read Naomi structured input files
`read_spectrum_projection_name()`	Read Spectrum Projection Name from Spectrum PJNZ
`read_spectrum_region_code()`	Read Subnational Region Code from Spectrum PJNZ
`read_spectrum_region_name()`	Read Subnational Region Name from Spectrum PJNZ
`report_tmb()`	Calculate Posterior Mean and Uncertainty Via TMB `sdreport()`
`sample_tmb()`	Sample TMB fit
`save_output()`	Save outputs to zip file
`save_output_package()` `read_output_package()`	Save outputs to zip file
`scale_gmrf_precision()`	Scale of GMRF precision matrix
`scatter_plotly()`	Plotly scatterplot data inputs and naomi outputs
`select_naomi_data()`	Select data for model fitting
`spread_areas()`	Spread area hierarchy to wide format
`subset_naomi_output()`	Subset the results returned in Naomi output package
`subset_output_package()`	Resave a subsetted Naomi output package
`survey_mf()`	Prepare model frames for survey datasets
`th_map()`	`ggplot2` theme for plotting maps
`validate_model_options()`	Validate a set of model options
`write_datapack_csv()`	Export naomi outputs to PEPFAR Data Pack format
`write_navigator_checklist()`	Write UNAIDS Estimates Navigator checklist CSV

Reference

All functions