Package index • malclimsim

All functions

MCMC_diag(): MCMC Diagnostic and Summary Plots with Save Options

build_priors(): Build a list of mcstate::pmcmc_parameter() objects, starting from the return_default_priors() template and then layering on any overrides.

calc_decay_arr(): Calculate Normalized SMC Decay Array Over Time

calculate_360_day_difference(): Calculate the Day Difference Assuming a 360-Day Year

calculate_estimate(): Calculate Outcome Across Matched Simulation Lists

calculate_monthly_metrics(): Compute monthly metrics from SMC schedule

calculate_weekly_metrics(): Compute weekly metrics from SMC schedule (epidemiological weeks, starting Sunday)

climate_to_30_day_months(): Convert Climate Data to 360-Day Years

compartments_sim(): Simulate Compartments Over Time with Prewarm Period

compute_climate_lead_days(): Compute how many days Climate must lead SMC

create_mcmc_params(): Create Adaptive Proposal and MCMC Control Parameters

create_proposal_matrix(): Create a Proposal Matrix

create_start_values(): Create Starting Values for Parameters

daily_smooth_rain(): Smooth Daily Rainfall Data

daily_smooth_temp(): Daily Smoothed Temperature Function

data_sim(): Simulate Incidence Data Over Time (Monthly or Weekly)

data_sim_for_inference(): Simulate Data for Inference

date_to_months(): Convert Date Range to Monthly Format

date_to_weeks(): Convert Date Range to Weekly Format (Sundays)

date_to_weeks_360(): Generate weekly model dates (by 7-day blocks) in 360-day calendar

decay_SMC(): Compute SMC Efficacy Decay Over Time

define_mcmc_control(): Define MCMC Control Settings

define_transformations(): Define Transformation Function for MCMC Simulation

evaluate_multiple_scenarios(): Evaluate Multiple SMC Scenarios

export_param_table_tex(): Export Estimated and Fixed Parameters to LaTeX

extend_inputs_with_prewarm(): Prepend Prewarm Climate to Your True Analysis Series

extend_time_varying_inputs(): Extend Time-Varying Inputs Backwards in Time

extend_time_varying_inputs_to_length(): Extend Time-Varying Inputs to Match Simulation Duration

extract_era5(): Extract Temperature Data from ERA5 File

extract_max_posterior_params(): Extract Parameters with Maximum Log Posterior

extract_vcv(): Extract Variance-Covariance Matrix and Restart Values

filter_by_year(): Filter a dataset by a range of years

filter_data(): Relate Time Steps to Observed Data for mcstate

filter_data_setup(): Set Up Filtered Data for Likelihood Evaluation

filter_incidence_by_dates(): Filter Incidence Data by Date Range

gen_smc_schedule(): Generate an SMC deployment schedule with optional month-specific coverages

generate_360_day_dates(): Generate Dates for a 360-Day Year Calendar

generate_comparison_function(): Generate Model-Observation Comparison Function

generate_smc_coverage_matrix(): Generate SMC Coverage Matrix for Simulation

generate_synthetic_data(): Generate Synthetic Incidence Data (Optional)

get_field_mapping(): Get Model Output Field Names for Observation Function

get_observation_function(): Get Observation Function Based on User Configuration

get_population_scaling(): Generate Vectors of Population Growth Scaling (r_C and r_A)

import_model(): Import an Odin Model into the malclimsim Package

impute_climate_to_end_date(): Impute Missing Climate Data Using Climatological Daily Means

index(): Create Index Mapping for Model Variables

inf_run(): Run MCMC Inference Simulation

initialize_observation_time(): Initialize Observation Time Index for Incidence Data

lag_and_trim_smc_climate(): Lag and Trim SMC and Climate Data.frames

load_clean_smc_data(): Load and clean raw SMC coverage data

load_model(): Loading an Odin Model

make_obs_config(): Create Observation Function Configuration

make_transform(): Create a Parameter Transformation Function

max_ll_post(): Extract and Print Maximum Log-Likelihood and Log-Posterior

model_date_360(): Convert model day index to calendar date assuming 360-day years

obs_cases: Observed Malaria Incidence Used for Model Calibration

plot_cases_averted_barplot(): Plot Cases Averted Across SMC Scenarios (with 95% Credible Intervals)

plot_chains(): Convert MCMC Output to List of Chains for Visualization

plot_compartments(): Plot Compartmental Simulation Results

plot_corr(): Plot Correlation of MCMC Samples

plot_estimate_distribution(): Plot Histogram of Estimated Effects with Confidence Interval and Trimmed X-Axis

plot_ppc(): Plot Posterior Predictive Check (PPC)

plot_ppc_single(): Plot Single Time Series Comparison (Uncomplicated or Severe Cases)

plot_priors(): Plot Default Priors

plot_time_series(): Plot Time Series of Malaria Incidence (Raw and Transformed)

post_plot(): Plot Posterior Distributions of Estimated Parameters

prepare_ppc_data(): Combine Posterior Simulations, Deterministic Prediction, and Observed Data for PPC Plotting

process_climate_data(): Process and Format Climate Data for Modeling

reorder_start_values(): Reorder MCMC Start Values to Match Prior Specification

return_default_priors(): Return Default Priors Used for Inference Procedure

run_mcmc_simulation(): Run MCMC Simulation

run_mcmc_simulations(): Run Model Simulations for Each Parameter Set

run_simulation_with_prewarm(): Run Model Simulation with Pre-Warm Period

run_simulations_from_samples(): Run Simulations from Sampled Parameter Sets

sample_mcmc_steps(): Sample Parameter Sets from MCMC Results

save_climate_data(): Saving Climate Data From ERA5 and CHIRTSdaily

save_era5(): Save ERA5 Reanalysis Data

save_plot_dynamic(): Save ggplot with Dynamic Filename

save_scenario_summary_tex(): Save LaTeX Table of Scenario Estimates

sim_mod(): Simulate the Malaria Model Over Time

simulate_best(): Run the model once at the maximum-posterior parameter set (deterministic)

simulate_models(): Simulate Models Using Sampled Parameters

simulate_with_max_posterior_params(): Simulate Model Using Parameters with Maximum Log Posterior

smc_data_raw: Raw SMC Coverage Data from CPS

smc_schedule_from_data(): Generate SMC Coverage and Decay Schedule

summarize_simulation_ci(): Create Long Format Data for Simulated Posterior Median and CI

summarize_simulations(): Summarize Simulation Outputs with Medians and Confidence Intervals

update_inf_stage(): Update proposal matrix, start values, and MCMC settings for next stage

update_param_list(): Update a Parameter List with New Values

update_priors(): Update Default Priors

validate_smc_climate_alignment(): Validate SMC and Climate for Lagged Alignment

view_priors(): View Details of Specified Priors