R: Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order

# Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order

## Documentation for package ‘pnd’ version 0.1.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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
GenD | Numerical derivative matrices with parallel capabilities
generateGrid | Create a grid of points for a gradient / Jacobian
generateGrid2 | Generate grid points for Hessians
Grad | Gradient computation with parallel capabilities
gradstep | Automatic step selection for gradients
Hessian | Numerical Hessians
Jacobian | Jacobian matrix computation with parallel capabilities
plot.gradstep | Step-size selection visualisation
plot.stepsize | Step-size selection visualisation
print.checkDimensions | Determine function dimensionality and vectorisation
print.GenD | Numerical derivative matrices with parallel capabilities
print.gradstep | Automatic step selection for gradients
print.Hessian | Numerical Hessians
print.stepsize | Automatic step selection for gradients
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.plugin | Plug-in step selection
step.SW | Stepleman-Winarsky automatic step selection
stepx | Default step size at given points