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.

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