Serial Interval and Case Reproduction Number Estimation


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Documentation for package ‘mitey’ version 0.2.0

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calculate_bootstrap_ci Calculate Bootstrap Confidence Intervals for R Estimates
calculate_r_estimates Calculate Reproduction Number Estimates
calculate_si_probability_matrix Calculate Serial Interval Probability Matrix
calculate_truncation_correction Calculate Right-Truncation Correction Factors
conv_tri_dist Convolution of the triangular distribution with the mixture component density (continuous case)
create_day_diff_matrix Create Day Difference Matrix
f0 Calculate f0 for Different Components
flower Calculate flower for Different Components
fupper Calculate fupper for Different Components
f_gam Calculate serial interval mixture density assuming underlying gamma distribution
f_norm Calculate serial interval mixture density assuming underlying normal distribution
generate_case_bootstrap Generate Bootstrap Sample of Case Incidence
generate_synthetic_epidemic Generate Synthetic Epidemic Data Using the Renewal Equation
integrate_component Integrate Serial Interval Component Functions for Likelihood Calculation
integrate_components_wrapper Compute Serial Interval Component Integrals for All Transmission Routes
plot_si_fit Visualize Serial Interval Distribution Fit to Outbreak Data
si_estim Estimate Serial Interval Distribution Using the Vink Method
smooth_estimates Apply Moving Average Smoothing to R Estimates
wallinga_lipsitch Estimate Time-Varying Case Reproduction Number Using Wallinga-Lipsitch Method
weighted_var Calculate Sample Weighted Variance
wt_loglik Calculate Weighted Negative Log-Likelihood for Gamma Distribution Parameters