permControl-deprecated: How to define a permutation design?

Description

Utility functions to describe unrestricted and restricted permutation designs for time series, line transects, spatial grids and blocking factors.

Usage

permControl(within = Within(), plots = Plots(), blocks = NULL,
            nperm = 199, complete = FALSE, maxperm = 9999,
            minperm = 99, all.perms = NULL, observed = FALSE)

Arguments

within, plots, blocks

Permutation designs for samples within the levels of plots (within), permutation of plots themselves, or for the definition of blocking structures which further restrict permutations (blocks)

nperm

the number of permutations.

complete

logical; should complete enumeration of all permutations be performed?

maxperm

the maximum number of permutations to perform. Currently unused.

minperm

the lower limit to the number of possible permutations at which complete enumeration is performed. See argument complete and Details, below.

all.perms

an object of class allPerms, the result of a call to allPerms.

observed

logical; should the observed permutation be returned as part of the set of all permutations?

Value

For permControl a list with components for each of the possible arguments.

Details

Argument mirror determines whether grid or series permutations can be mirrored. Consider the sequence 1,2,3,4. The relationship between consecutive observations is preserved if we reverse the sequence to 4,3,2,1. If there is no inherent direction in your experimental design, mirrored permutations can be considered part of the Null model, and as such increase the number of possible permutations. The default is to not use mirroring so you must explicitly turn this on using mirror = TRUE in permControl.

To permute plots rather than the observations within plots (the levels of strata), use Within(type = "none") and Plots(type = foo), where foo is how you want the plots to be permuted. However, note that the number of observations within each plot must be equal!

For some experiments, such as BACI designs, one might wish to use the same permutation within each plot. This is controlled by argument constant. If constant = TRUE then the same permutation will be generated for each level of strata. The default is constant = FALSE.

References

shuffle() is modelled after the permutation schemes of Canoco 3.1 (ter Braak, 1990); see also Besag & Clifford (1989).

Besag, J. and Clifford, P. (1989) Generalized Monte Carlo significance tests. Biometrika 76; 633--642.

ter Braak, C. J. F. (1990). Update notes: CANOCO version 3.1. Wageningen: Agricultural Mathematics Group. (UR).