GenD                    Numerical derivative matrices with parallel
                        capabilities
Grad                    Gradient computation with parallel capabilities
Jacobian                Jacobian matrix computation with parallel
                        capabilities s Computes the numerical Jacobian
                        for vector-valued functions. Its columns are
                        partial derivatives of the function with
                        respect to the input elements. This function
                        supports both two-sided (central, symmetric)
                        and one-sided (forward or backward)
                        derivatives. It can utilise parallel processing
                        to accelerate computation of gradients for slow
                        functions or to attain higher accuracy faster.
                        Currently, only Mac and Linux are supported
                        'parallel::mclapply()'. Windows support with
                        'parallel::parLapply()' is under development.
alignStrings            Align printed output to the longest argument
checkCores              Number of core checks and changes
checkDimensions         Determine function dimensionality and
                        vectorisation
dupRowInds              Repeated indices of the first unique value
fdCoef                  Finite-difference coefficients for arbitrary
                        grids
formatMat               Round a matrix to N signifcant digits in mixed
                        FP/exp notation
generateGrid            Create a grid of points for a gradient /
                        Jacobian
generateGrid2           Generate grid points for Hessians
gradstep                Automatic step selection for gradients
plot.stepsize           Step-size selection visualisation
print.Hessian           Numerical Hessians
printMat                Print a matrix with separators
runParallel             Run a function in parallel over a list
                        (internal use only)
solveVandermonde        Numerically stable non-confluent Vandermonde
                        system solver
step.CR                 Curtis-Reid automatic step selection
step.DV                 Dumontet-Vignes automatic step selection
step.K                  Kink-based step selection
step.M                  Mathur's AutoDX-like automatic step selection
step.SW                 Stepleman-Winarsky automatic step selection
step.plugin             Plug-in step selection
stepx                   Default step size at given points
