Read and write 'GraphPad Prism' '.pzfx' files in R.

Mortality rates are typically provided in an abridged format, i.e., by age groups 0, [1, 5], [5, 10]', '[10, 15]', and so on. Some applications necessitate a detailed (single) age description. Despite the large number of proposed approaches in the literature, only a few methods ensure great performance at both younger and higher ages. For example, the 6-term 'Lagrange' interpolation function is well suited to mortality interpolation at younger ages (with irregular intervals), but not at older ages. The 'Karup-King' method, on the other hand, performs well at older ages but is not suitable for younger ones. Interested readers can find a full discussion of the two stated methods in the book Shryock, Siegel, and Associates (1993).The Q2q package combines the two methods to allow for the interpolation of mortality rates across all age groups. It begins by implementing each method independently, and then the resulting curves are linked using a 5-age averaged error between the two partial curves.

Construct message-passing style objects with types and features. Q7 types uses composition instead of inheritance in creating derived types, allowing defining any code segment as feature and associating any feature to any object. Compared to R6, Q7 is simpler and more flexible, and is more friendly in syntax.

A copula-based measure for quantifying asymmetry in dependence and associations. Documentation and theory about 'qad' is provided
    by the paper by Junker, Griessenberger & Trutschnig (2021, <doi:10.1016/j.csda.2020.107058>), and the paper by Trutschnig (2011, <doi:10.1016/j.jmaa.2011.06.013>).

The Ensemble Quadratic and Affine Invariant Markov chain Monte 
    Carlo algorithms provide an efficient way to perform Bayesian inference in 
    difficult parameter space geometries. The Ensemble Quadratic Monte Carlo 
    algorithm was developed by Militzer (2023) <doi:10.3847/1538-4357/ace1f1>. 
    The Ensemble Affine Invariant algorithm was developed by Goodman and Weare 
    (2010) <doi:10.2140/camcos.2010.5.65> and it was implemented in Python by 
    Foreman-Mackey et al (2013) <doi:10.48550/arXiv.1202.3665>. The Quadratic 
    Monte Carlo method was shown to perform better than the Affine Invariant 
    method in the paper by Militzer (2023) <doi:10.3847/1538-4357/ace1f1> and 
    the Quadratic Monte Carlo method is the default method used. The Chen-Shao 
    Highest Posterior Density Estimation algorithm is used for obtaining 
    credible intervals and the potential scale reduction factor diagnostic is 
    used for checking the convergence of the chains.