stepit: Compute a new step size for a linear search within an...

View source: R/stepit.R

stepitR Documentation

Compute a new step size for a linear search within an optimization algorithm.

Description

Using cubic interpolation, a new step size is computed for minimizing a function value.

Usage

  stepit(linemat, ips, dblwrd, MAXSTEP)

Arguments

linemat

A 3 by 5 matrix containing step sizes, function values and slopes at multiple values.

ips

If 1, previous slope was positive.

dblwrd

Vector of length 2: dblwrd[1] TRUE means step halved dblwrd[2] TRUE means step doubled.

MAXSTEP

maximum allowed size of a step.

Value

A positive step size.

References

Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.


fda documentation built on Sept. 30, 2024, 9:19 a.m.