ojaMedianControl: Tuning Parameters for the Function 'ojaMedian'
In OjaNP: Multivariate Methods Based on the Oja Median and Related Concepts

Description Usage Arguments Author(s) See Also Examples

Tuning parameters for the algorithms used by function ojaMedian.

ojaMedianControl(sigmaInit = 0, sigmaAda = 20, adaFactor = 0.5, 
                  iter = 1e+06, useAllSubsets = FALSE, 
                  nSubsetsUsed = 1000, sigmaLog10Dec = 10, 
                  storeSubDet = TRUE, eps = 0.1, chi2 = 0.95, 
                  samples = 20, maxlines = 1000, S1 = cov, 
                  S2 = cov4, S1args = list(), S2args = list(),
                  volume = 1e-6, boundedExact = T, ...)

`sigmaInit`	(for the `evo` algorithm): Set the initial variance of the mutation vector in the first run.
`sigmaAda`	(for the `evo` algorithm): Defines after how many mutations the variance of the mutation vector is adjusted.
`adaFactor`	(for the `evo` algorithm): Defines the level of adjustment of the mutation vector.
`iter`	(for the `evo` algorithm): The maximum number of iterations. If the algorithm does not converge, it stops after `iter` - iterations.
`useAllSubsets`	(for the `evo` algorithm): A logical flag. If it is set all datapoints and resulting simplices are taken into account for the calculation.
`nSubsetsUsed`	(for the `evo` algorithm): If useAllSubsets is not set, this determines how many, randomly selected, datapoints are taken into account.
`sigmaLog10Dec`	(for the `evo` algorithm): This is an abort criterion. If the logarithmised initial variance differs more than sigmaLog10Dec from the actual, logarithmised variance, the algorithm stops.
`storeSubDet`	(for the `evo` algorithm): A boolean flag. If it is set subdeterminants are stored. This should always been set to `TRUE` if 6(dim -1)nSubsetsUsed<CPU-Cache.
`eps`	(for the `grid` algorithm): This is the abort criterion. If the grid becomes denser than this threshold the algorithm stops.
`chi2`	(for the `grid` algorithm): This is the test niveau of the test, if a grid point could be used as a Oja-Median or not.
`samples`	(for the `grid` algorithm): This determines how many additional hyperplanes are taken after every run.
`maxlines`	(for the `exact` algorithm): This determines how many intersection lines are investigated in addtion to the one with the steepest gradient.
`S1`	(for the `evo` and `grid` algorithms): Passed on to `ics` to compute the invariant coordinate system. Default is `cov`.
`S2`	(for the `evo` and `grid` algorithms): Passed on to `ics` to compute the invariant coordinate system. Default is `cov4`.
`S1args`	(for the `evo` and `grid` algorithms): Optional arguments for `S1` passed on to `ics` to compute the invariant coordinate system.
`S2args`	(for the `evo` and `grid` algorithms): Optional arguments for `S2` passed on to `ics` to compute the invariant coordinate system.
`volume`	(for the `bounded_exact` algorithm): is the desired size of the bounded region, which is selected as a part of the original volume. Here the volume is calculated as the volume of a minimal multivariate circumscribed rectangle with edges parallel to the coordinate axes.
`boundedExact`	(for the `bounded_exact` algorithm): setting this parameter to `FALSE` stops the algorithm after the bounded region is found, and its center is reported as an approximation of the median.
`...`	Additional hidden option