NNS (version 11.3)

NNS.diff: NNS Numerical Differentiation

Description

Determines numerical derivative of a given univariate function using projected secant lines on the y-axis. These projected points infer finite steps h, in the finite step method.

Usage

NNS.diff(f, point, h = 0.1, tol = 1e-10, digits = 12, print.trace = FALSE)

Value

Returns a matrix of values, intercepts, derivatives, inferred step sizes for multiple methods of estimation.

Arguments

f

an expression or call or a formula with no lhs.

point

numeric; Point to be evaluated for derivative of a given function f.

h

numeric [0, ...]; Initial step for secant projection. Defaults to (h = 0.1).

tol

numeric; Sets the tolerance for the stopping condition of the inferred h. Defaults to (tol = 1e-10).

digits

numeric; Sets the number of digits specification of the output. Defaults to (digits = 12).

print.trace

logical; FALSE (default) Displays each iteration, lower y-intercept, upper y-intercept and inferred h.

Author

Fred Viole, OVVO Financial Systems

References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" (ISBN: 1490523995)

Examples

if (FALSE) {
f <- function(x) sin(x) / x
NNS.diff(f, 4.1)
}