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Made changes to account for the upcoming stringsAsFactors = FALSE default argument to data.frame() in R 4.0 so that the package is backwards compatible.
Change to unit test to allow for a tolerance when comparing floating points and a fix for a warning thrown from r-devel.
Hotfix to address new sample
implementation forthcoming
in R 3.6.0. Currently the warning is being suppressed, but the unit
tests will be updated once these changes have been implemented in stable
R.
Minor documentation fixes, with the main one being correcting the name of the Diagnostics vignette.
Major overhaul to the API with non-backwards compatible changes. The primary change is that both the incidence and survival models are now specifiable, in contrast to the previous version which forced a homogeneous Poisson process incidence model and a Weibull survival model that uses age and sex as covariates. These models are retained as defaults, but the user can provide custom objects for both these processes, as documented in the User Guide.
A number of small basic functions mostly relating to diagnostics have been removed to condense the API.
See the User Guide vignette for examples of the new parameterisation
of prevalence
and general documentation.
raw_incidence
to yearly_incidence
This function has been renamed to be more descriptive of what the
function actually does, and reparameterised to allow the user to specify
the ending date of the time interval of interested instead.
raw_incidence
is still included but it throws a deprecated
warning and suggests the use of yearly_incidence
determine_registry_years
to
determine_yearly_limits
The original function name isn’t very descriptive for what it does
(provides the yearly end points of a specific time interval) and so have
renamed it to better reflect its purpose.
determine_yearly_limits
has a slighlty different argument
list to determine_registry_years
to allow for the
specification of the closing date in the interval rather than the
opening.
prevalence
no longer runs the simulation when there is
more registry data available than needed to estimate N-year
prevalenceprevalence
no longer requires a population size as an
argument. Absolute prevalence is always calculated, with relative rates
provided if population size is specifieduser_manual
: Updated to include a link to the specific
webpage where the ONS data set is obtained from and improved
formattingsummary.prevalence
correctly displays posterior age
distributions of simulated cases and now displays the prevalence
estimates themselvesBug hotfix.
The posterior age distribution, returned from prevalence
as in the simulated
object, is now stored in the format of
a nested list rather than a matrix as before. The first dimension of the
list corresponds to each sex (if applicable), the next indexing the
number of years of simulated cases, and the final corresponds to the
bootstrap samples. The final level comprises a vector holding the ages
of the simulated cases which are still contributing to prevalence at the
index date from the corresponding sex, year, and bootstrap sample
number.
Minor bug fixes and a slight change to the parameterisation of prevalence:
First release of the package, working with all features necessary to provide estimates of point prevalence. Issues which we’d like to address in future releases are:
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.