R: Secondary functions for neldermead.search

Secondary search functions {neldermead}

R Documentation

Secondary functions for neldermead.search

Description

Utility functions for neldermead.serch and dependent functions.

Usage

  neldermead.startup(this = NULL)
  neldermead.log(this = NULL, msg = NULL)
  neldermead.scaletox0(this = NULL, simplex0 = NULL)
  neldermead.scaletocenter(this = NULL, simplex0 = NULL, x0 = NULL)
  neldermead.termstartup(this = NULL)
  neldermead.outputcmd(this = NULL, state = NULL, simplex = NULL, step = NULL)
  neldermead.autorestart(this = NULL)
  neldermead.istorestart(this = NULL)
  neldermead.isroneill(this = NULL)
  neldermead.isrkelley(this = this)
  neldermead.updatesimp(this = NULL)
  scaleinconstraints(this = NULL, x = NULL, xref = NULL)
  neldermead.costf(x = NULL, this = NULL)

Arguments

`this`	A neldermead object.
`msg`	A character string.
`simplex0`	The initial simplex object.
`x0`	A column matrix of initial parameters.
`state`	The state of the algorithm, either 'init', 'done' or 'iter'.
`simplex`	The current simplex object.
`step`	The type of step performed during the iteration: 'init', 'done', 'reflection', 'expansion', 'insidecontraction', 'outsidecontraction', 'reflectionnext' or 'shrink'.
`x`	The point estimate to scale.
`xref`	The reference point estimate.

Details

neldermead.startup: Startup the algorithm. Compute the initial simplex, depending on the content of the simplex0method element of the neldermead object ('given', 'axes', 'spendley', 'pfeffer' or 'randbounds').
neldermead.log: Print a message to the log file using optimbase.log.
neldermead.scaletox0: Scale the simplex into the nonlinear inequality constraints, if any. Scale toward x0, which is feasible.
neldermead.scaletocenter: Scale the simplex into the nonlinear inequality constraints, if any. Scale to the centroid of the points which satisfy the constraints. This is Box's method for scaling. It is unsure, since the centroid of the points which satisfy the constraints may not be feasible.
neldermead.termstartup: Initialize Kelley's stagnation detection system when normalization is required, by computing kelleyalpha. If the simplex gradient is zero, then use alpha0 as alpha.
neldermead.outputcmd: Call the array of user-defined output functions
neldermead.autorestart: Perform an optimization with automatic restart. The loop processes for i = 1 to restartmax + 1. This is because a RE-start is performed after one simulation has been performed, hence the 'RE'.
neldermead.istorestart: Determine if the optimization is to restart using neldermead.isroneill or neldermead.isrkelley depending on the content of the restartdetection element.
neldermead.isroneill: Determine if the optimization is to restart. Use O'Neill method as a criteria for restart. It is an axis-by-axis search for optimality.
neldermead.isrkelley: Determine if the optimization is to restart. Use kelleystagnation as a criteria for restart.
neldermead.updatesimp: Update the initial simplex simplex0 for a restart.
scaleinconstraints: Given a point reference to scale and a reference point which satisfies the constraints, scale the point towards the reference point estimate until it satisfies all the constraints.
neldermead.costf: Call the cost function and return the value. This function is given to the simplex function class as a callback. Input/Output arguments are swapped w.r.t. optimbase.function, so that it matches the requirements of simplex methods.

Value

neldermead.startup

Return an updated neldermead object this.

neldermead.log

Return the neldermead object this.

neldermead.scaletox0

Return an updated simplex.

neldermead.scaletocenter

Return an updated simplex.

neldermead.termstartup

Return an updated neldermead object this.

neldermead.outputcmd

Do not return any data, but execute the output function(s).

neldermead.autorestart

Return an updated neldermead object this.

neldermead.istorestart