R: Implements Empirical Bayes Incidence Curves

# Implements Empirical Bayes Incidence Curves

## Documentation for package ‘incidental’ version 0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

compute_expected_cases | Compute expected cases
compute_log_incidence | Compute log likelihood of incidence model
covid_delay_dist | Delay distribution from COVID-19 pandemic.
covid_new_york_city | New York City data from the COVID-19 pandemic.
data_check | Input data check
data_processing | Data processing wrapper
diff_trans | Transpose of the 1st difference operator
fit_incidence | Fit incidence curve to reported data
front_zero_pad | Pad reported data with zeros in front
incidence_to_df | Export incidence model to data frame
init_params | Initialize spline parameters (beta)
make_ar_extrap_samps | Make AR samples for extrapolation past end point
make_likelihood_matrix | Make delay likelihood matrix
make_spline_basis | Create spline basis matrix
marg_loglike_poisson | Marginal log likelihood This function computes the marginal probability of Pr(reported | beta). Note that lnPmat must be zero padded enough (or censored) to match the length of reported cases vector.
marg_loglike_poisson_fisher | Marginal log likelihood Fisher information matrix
marg_loglike_poisson_grad | Marginal log likelihood gradient
plot.incidence_spline_model | Plot model from fit_incidence
poisson_objective | Poisson objective function
poisson_objective_grad | Poisson objective function gradient
poisson_objective_post_cov_approx | Compute Fisher information matrix for Poisson objective
regfun | Beta regularization function
regfun_grad | Beta regularization function gradient
regfun_hess | Beta regularization function Hessian
sample_laplace_log_incidence_poisson | Generate Laplace samples of incidence
scan_spline_dof | Scan spline degrees of freedom
scan_spline_lam | Scan spline regularization parameter
spanish_flu | Daily flu mortality from 1918 flu pandemic.
spanish_flu_delay_dist | Delay distribution from 1918 flu pandemic.
train_and_validate | Train and validate model on reported data
train_val_split | Split reported case data