NNS.diff: NNS Numerical Differentiation

Description Usage Arguments Value Author(s) References Examples

View source: R/Numerical_Differentiation.R

Description

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

Usage

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

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. Defualts to (tol=1e-10).

print.trace

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

Value

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

Author(s)

Fred Viole, OVVO Financial Systems

References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" http://amzn.com/1490523995

Examples

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f<- function(x) sin(x)/x
NNS.diff(f,4.1)

g<- function(x) sin(x)
NNS.diff(g,1)

NNS documentation built on May 19, 2017, 10 a.m.

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