The way grobs are defined in the method plot for objects of class SAI has been modified to accomodate some changes made in new versions of ggplot2 (>=3.5.0).
A bug in the function annual2quaterly has been fixed when its input annual life table is defined using death rates (mx).
The previous version (0.0.1-15) of qlifetable just computes from
microdata the summary statistics to build quarterly life tables. This
new version includes two new sets of functions. On the one hand,
qlifetable now incorporates a bunch of functions to
construct from summary statistics Seasonal-ageing indexes (SAIs) and
quarterly life tables and, on the other hand, the new version also has
new functions to estimate SAIs approximations as detailed in Pavía and
Lledó (2023) doi:10.1017/asb.2023.16.
The list of new functions includes:
annual2quarterly. This function allows to derive the four quarterly life tables associated with an annual life table by employing a set of estimated SAIs that have been obtained using either the new function compute_SAI or SAI_shortcut_1.
compute_SAI. This function computes the seasonal-ageing index (SAIs) estimates linked to a set of quarterly crude rates of mortality, attained using either crude_mx, crude_mx_sh2 or crude_mx_sh3, corresponding to several years.
crude_mx. This function computes quarterly crude rates of mortality given (i) a set of quarterly datasets of time of expositions at risk and (ii) a dataset of quarterly deaths.
crude_mx_sh2. This function computes, by applying equation (2.7) in Pavía and Lledó (2023), quarterly crude rates of mortality given (i) a couple of integer-age stock of population datasets and (ii) a dataset of quarterly deaths.
crude_mx_sh3. This function computes, by applying equation (2.9) in Pavía and Lledó (2023), quarterly crude rates of mortality given (i) a couple of integer-age stock of population datasets, (ii) a dataset of quarterly deaths, (iii) a dataset of quarterly entries and (iv) a dataset of quarterly exits.
plot.SAI. This function is a method for plotting
objects of the class SAI attained using either the function
compute_SAI or SAI_shortcut_1.
SAI_shortcut_1. This function estimates a set of SAIs by applying equation (2.5) in Pavía and Lledó (2023) given a set of datasets of quarterly deaths.