incidental0.1 package

Implements Empirical Bayes Incidence Curves

compute_expected_cases

Compute expected cases

compute_log_incidence

Compute log likelihood of incidence model

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

incidental

incidental: A package for computing incidence curves from delayed case...

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 probabilit...

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

Make empirical Bayes incidence curves from reported case data using a specified delay distribution.

  • Maintainer: Lauren Hannah
  • License: MIT + file LICENSE
  • Last published: 2020-09-16