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.

Finite Difference Method for Multi-Asset Option Valuation
Efficient finite difference method for valuing European and American multi-asset options.

Implements a generalization of the Cochran-Armitage trend test to
multinomial data. In addition to an overall test, multiple testing adjusted
p-values for trend in individual outcomes and power calculation is
available.

Collinearity Detection in a Multiple Linear Regression Model
The detection of worrying approximate collinearity in a multiple linear regression model is a problem addressed in all existing statistical packages. However, we have detected deficits regarding to the incorrect treatment of qualitative independent variables and the role of the intercept of the model. The objective of this package is to correct these deficits. In this package will be available detection and treatment techniques traditionally used as the recently developed.
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C. Garcia, R. Salmeron and C.B. Garcia (2019) <doi:10.1080/00949655.2018.1543423>.
R. Salmeron, C.B. Garcia and J. Garcia (2018) <doi:10.1080/00949655.2018.1463376>.
G.W. Stewart (1987) <doi:10.1214/ss/1177013444>.