GEE solver for correlated nominal or ordinal multinomial responses
    using a local odds ratios parameterization.

Provides a multi action button for usage in 'shiny'
    applications.

The base apply function and its variants, as well as the related
    functions in the 'plyr' package, typically apply user-defined functions to a
    single argument (or a list of vectorized arguments in the case of mapply). The
    'multiApply' package extends this paradigm with its only function, Apply, which
    efficiently applies functions taking one or a list of multiple unidimensional
    or multidimensional arrays (or combinations thereof) as input. The input
    arrays can have different numbers of dimensions as well as different dimension
    lengths, and the applied function can return one or a list of unidimensional or
    multidimensional arrays as output. This saves development time by preventing the
    R user from writing often error-prone and memory-inefficient loops dealing with
    multiple complex arrays. Also, a remarkable feature of Apply is the transparent
    use of multi-core through its parameter 'ncores'. In contrast to the base apply
    function, this package suggests the use of 'target dimensions' as opposite
    to the 'margins' for specifying the dimensions relevant to the function to be
    applied.

Efficient finite difference method for valuing European and American multi-asset options.

Estimation routines for several classes of affine term structure of interest rates models. All the models are based on the single-country unspanned macroeconomic risk framework from Joslin, Priebsch, and Singleton (2014, JF) <doi:10.1111/jofi.12131>. Multicountry extensions such as the ones of Jotikasthira, Le, and Lundblad (2015, JFE) <doi:10.1016/j.jfineco.2014.09.004>, Candelon and Moura (2023, EM) <doi:10.1016/j.econmod.2023.106453>, and Candelon and Moura (Forthcoming, JFEC) <doi:10.1093/jjfinec/nbae008> are also available.

Computationally efficient functions to provide direct likelihood-based
    inference for partially-observed multivariate birth-death processes.  Such processes
    range from a simple Yule model to the complex susceptible-infectious-removed model
    in disease dynamics.  Efficient likelihood evaluation facilitates maximum likelihood
    estimation and Bayesian inference.