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