| 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 |