Package index
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calculate_bootstrap_ci() - Calculate Bootstrap Confidence Intervals
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calculate_r_estimates() - Calculate R From Incidence and Serial Interval
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calculate_si_probability_matrix() - Calculate Serial Interval Probability Matrix
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calculate_truncation_correction() - Calculate Right Truncation Correction
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conv_tri_dist() - Convolution of the triangular distribution with the mixture component density (continuous case)
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create_day_diff_matrix() - Create Day Difference Matrix
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f0() - Calculate f0 for Different Components
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f_gam() - Helper function to plot the fit of the serial interval distribution assuming an underlying gamma distribution
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f_norm() - Helper function to plot the fit of the serial interval distribution assuming an underlying normal distribution
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flower() - Calculate flower for Different Components
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fupper() - Calculate fupper for Different Components
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generate_case_bootstrap() - Generate Case Bootstrap Sample
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generate_synthetic_epidemic() - Generate synthetic incidence data from a known reproduction number
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integrate_component() - Integrate Component Function
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integrate_components_wrapper() - Wrapper function to for integrate_components()
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plot_si_fit() - Plot the epidemic curve and fitted serial interval distribution
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si_estim() - Estimate serial interval using the EM Algorithm as developed by Vink et al. (2014)
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smooth_estimates() - Apply Smoothing to Estimates
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wallinga_lipsitch() - Estimate time-varying reproduction number using Wallinga-Lipsitch method with bootstrap confidence intervals
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weighted_var() - Calculate weighted variance
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wt_loglik() - weighted likelihood for optimising parameters assuming underlying gamma distribution each point adds to likelihood given weight belonging to component 2: w2