R: Baseline Nowcasting for Right-Truncated Epidemiological Data

# Baseline Nowcasting for Right-Truncated Epidemiological Data

## Documentation for package ‘baselinenowcast’ version 0.2.0

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

## Help Pages

allocate_reference_times | Allocate training volume based on combination of defaults and user-specified values for training volume for delay and uncertainty estimation.
apply_delay | Apply the delay to generate a point nowcast
apply_reporting_structure | Apply reporting structure to generate a single retrospective reporting triangle
apply_reporting_structures | Apply reporting structures to generate retrospective reporting triangles
as.data.frame.reporting_triangle | Convert reporting_triangle to data.frame
as.matrix.reporting_triangle | Convert reporting_triangle to plain matrix
assert_baselinenowcast_df | Assert validity of 'baselinenowcast_df' objects
assert_reporting_triangle | Assert validity of 'reporting_triangle' objects
as_ChainLadder_triangle | Convert reporting_triangle to ChainLadder triangle format
as_reporting_triangle | Create a 'reporting_triangle' object
as_reporting_triangle.data.frame | Create a 'reporting_triangle' object from a data.frame
as_reporting_triangle.matrix | Create a 'reporting_triangle' from a matrix
as_reporting_triangle.triangle | Convert ChainLadder triangle to reporting_triangle format
baselinenowcast | Generate a nowcast
baselinenowcast.data.frame | Create a dataframe of nowcast results from a dataframe of cases indexed by reference date and report date
baselinenowcast.reporting_triangle | Create a dataframe of nowcast results from a single reporting triangle
baselinenowcast_df | Nowcast Data.frame Object
baselinenowcast_df-class | Nowcast Data.frame Object
combine_obs_with_pred | Combine observed data with a single prediction draw
estimate_and_apply_delay | Estimate and apply delay from a reporting triangle
estimate_and_apply_delays | Estimate and apply delays to generate retrospective nowcasts
estimate_and_apply_uncertainty | Estimate and apply uncertainty to a point nowcast matrix
estimate_delay | Estimate a delay distribution from a reporting triangle
estimate_uncertainty | Estimate uncertainty parameters
estimate_uncertainty_retro | Estimate uncertainty parameters using retrospective nowcasts
example_downward_corr_rt | Example reporting triangle with downward corrections
example_reporting_triangle | Simple example reporting triangle for demonstrations
fit_by_horizon | Helper function that fits its each column of the matrix (horizon) to an observation model.
fit_nb | Fit a negative binomial to a vector of observations and expectations
germany_covid19_hosp | Incident COVID-19 hospitalisations indexed by the date of positive test (reference date) and report date from Germany in 2021 and 2022.
get_delays_from_dates | Compute delays between report dates and reference dates
get_delays_unit | Get delays unit from a reporting triangle
get_max_delay | Get maximum delay from reporting_triangle
get_mean_delay | Get mean delay for each row of reporting_triangle
get_quantile_delay | Get quantile delay for each row of reporting_triangle
get_reference_dates | Get reference dates from reporting_triangle
get_reporting_structure | Get reporting structure from a reporting triangle
get_report_dates | Compute report dates from reference dates and delays
head.reporting_triangle | Get first rows of a reporting_triangle
is_reporting_triangle | Check if an object is a reporting_triangle
new_baselinenowcast_df | Combine data from a nowcast dataframe, strata, and reference dates
new_reporting_triangle | Class constructor for 'reporting_triangle' objects
preprocess_negative_values | Preprocess negative values in the reporting triangle
print.reporting_triangle | Print a reporting_triangle object
reporting_triangle | Reporting Triangle Object
reporting_triangle-class | Reporting Triangle Object
sample_nb | Sample from negative binomial model given a set of predictions
sample_nowcast | Generate a single draw of a nowcast combining observed and predicted values
sample_nowcasts | Generate multiple draws of a nowcast combining observed and predicted values
sample_prediction | Get a draw of only the predicted elements of the nowcast vector
sample_predictions | Get a dataframe of multiple draws of only the predicted elements of the nowcast vector
summary.reporting_triangle | Summarize a reporting_triangle object
syn_nssp_df | A synthetic dataset containing the number of incident cases indexed by reference date and report date. While data of this form could be from any source, this data is meant to represent the output of pre-processing the syn_nssp_line_list dataset, which is a synthetic patient-level line list data from the United State's National Syndromic Surveillance System (NSSP).
syn_nssp_line_list | A synthetic dataset resembling line-list (each row is a patient) data from the United States' National Syndromic Surveillance System (NSSP) accessed via the Essence platform. All entries are synthetic, formatted to look as close to the real raw data as possible.
tail.reporting_triangle | Get last rows of a reporting_triangle
truncate_to_delay | Truncate reporting triangle to a specific maximum delay
truncate_to_quantile | Truncate reporting_triangle to quantile-based maximum delay
truncate_to_row | Truncate reporting triangle by removing a specified number of the last rows
truncate_to_rows | Truncate reporting triangle by removing bottom rows
validate_reporting_triangle | Validate a reporting_triangle object
[.reporting_triangle | Subset reporting_triangle objects
[<-.reporting_triangle | Subset assignment for reporting_triangle objects