now using the new default random number generator in tests
updated tests to pass check with R 4.0.2; this includes re-generation of most reference objects, which were manually inspected and validated against old references
new function merge_projections permits to join different sets of
simulations, adapting the respective time windows accordingly
new function merge_add_projections permits to add simulated case incidence
from different sets of simulations, adapting the respective time windows
accordingly; if objects contain different numbers of simulations, the shortest
ones are recycled as needed; also implemented as the operator +
new function summary will summarise projections objects by day, using a
range of pre-defined statistics (mean, sd, min, max, and user-defined
quantiles)
bug fix for the use of time-varying R in project
bug fix for as.data.frame(..., long = TRUE)
more consistent handling of inputs for the serial interval; if provided as a
vector, si now starts at a delay of 1 day, rather than 0 and assuming the
first entry is 0; for distcrete inputs, the mass for si$d(0) is now
ignored, and the rest of the distribution is rescaled accorindly to ensure the
PMF sums to 1
(documentation) more realistic serial interval distribution used for the Ebola examples
(internal) the force of infection is now calculated by the new internal
function compute_force_infection
(testing) revised sets of tests relying less on comparison to references, but testing for meaningful output properties instead
(testing) 100% coverage
project can now use time-varying R by specifying time_change, a vector of
dates at which R changes, and providing a vector or a list of values for
R instead of a vector, in which case it needs to have length(time_change) + 1 components, each of which is a vector of R values.project() where R was being resampled recursively was fixed
(#11, @jarvisc1; #12, @zkamvar)get_dates() now inherits the generic get_dates() from incidenceThis is a big release! Plenty of new features have been added, including:
projections can now be subsetted like matrices using x[i,j], or using the
function subset
new function cumulate to compute cumulative incidence for projections
objects, akin to the similar function in the incidence package
much improved graphics; plot now call upons add_projections, which
implements many options for plotting projections, including quantiles lines,
ribbon, and boxplots; add_projections can also be used to add such plots to
an existing incidence plot
build_projections can be used to build a projections object from an input
matrix and optional dates
project can now use a Negative Binomial model as an alternative to the
original Poisson model to account for over-dispersion in new cases /
super-spreading.Fixed the calls to sample, which has a rather irrational behaviour when
passing a first argument of length 1 (i.e. not bootstrapping from the vector).
First release of the package!
project: a function generating projections from an existing incidence
object, a serial interval distribution, and a set of plausible reproduction
numbers ($R$); returns a projections object.
plot/print: plotting and printing methods for projections objects.
get_dates: accessors for projections objects.
as.data.frame: conversion from projections objects to data.frame.