-
aedseo()
is now deprecated. Please useseasonal_onset()
instead. A warning is shown when usingaedseo()
(#41). -
tsd()
is now deprecated. Please useto_time_series()
instead. A warning is shown when usingtsd()
(#41).
-
Added a new argument
only_current_season
toseasonal_onset()
,seasonal_burden_levels()
andcombined_seasonal_output()
which gives the possibility to either get output from only the current season or for all available seasons (#45). -
Added
combined_seasonal_output()
as the main function to run bothseasonal_onset()
andseasonal_burden_levels()
to get a combined result for the newest season (#44). -
Added
seasonal_onset()
as a replacement for the deprecatedaedseo()
function (#41). -
Added
to_time_series()
as a replacement for the deprecatedtsd()
function (#41). -
Added the
seasonal_burden_levels()
function, which calculates burden levels based on data from previous seasons with two different methods; "peak_levels" or "intensity_levels" (#37). -
Added the
fit_quantiles()
function, which optimises a user selected distribution and calculates the quantiles based on observations and weights. It is meant to be used within theseasonal_burden_levels()
function (#35, #37).
-
Improved the
epi_calendar()
function to work for a season spanning new year (#34). -
The
aedseo()
function now allows for the choice of adding season as an input argument (#34). -
{checkmate}
assertions have been added to enhance user feedback with clearer error messages and to ensure functions operate correctly by validating inputs (#33). -
Improved the
aedseo()
function to work withNA
values. The user now defines how manyNA
values the function should allow in each window (#32).
- The
disease_threshold
argument now reflects the disease threshold in one time step. If the total number of cases in a window of sizek
exceedsdisease_threshold * k
, a seasonal onset alarm can be triggered (#32).
- Transferring maintainership of the R package to Lasse Engbo Christiansen.
- Enhanced clarity and user guidance in the introductory vignette, providing a more comprehensive walkthrough of the application of the 'aeddo' algorithm on time series data with detailed explanations and illustrative examples.
-
Updated LICENSE.md to have Statens Serum Institut as a copyright holder.
-
Fixed installation guide for the development version in the README.Rmd and README.md
-
Added Lasse Engbo Christiansen as an author of the R package.
-
Added a new function
epi_calendar()
that determines the epidemiological season based on a given date, allowing users to easily categorize dates within or outside specified seasons. -
Introduced additional visualizations in the
autoplot()
method, enhancing the capabilities of theplot()
method with new displays of observed cases and growth rates.
-
Added the
aedseo
function, which automates the early detection of seasonal epidemic onsets by estimating growth rates for consecutive time intervals and calculating the Sum of Cases (sum_of_cases). -
Introduced
autoplot
andplot
methods for visualizingaedseo
andaedseo_tsd
objects. These functions allow you to create insightful ggplot2 plots for your data. -
Included the
fit_growth_rate
function, enabling users to fit growth rate models to time series observations. -
Introduced the
predict
method foraedseo
objects, which allows you to predict observations for future time steps given the growth rates. -
Added the
summary
method foraedseo
objects, providing a comprehensive summary of the results. -
Introduced the
tsd
function, allowing users to create S3aedseo_tsd
(time-series data) objects from observed data and corresponding dates.