### Package changes from previous qlifetable version 0.0.1-15

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.