sp: Multiresponse sequence procedure

In Blossom: Statistical Comparisons with Distance-Function Based Permutation Tests

Description

Multiresponse sequence procedure (MRSP) is a special case of MRPP where first-order sequential pattern of data is tested against the null hypothesis of no sequential pattern. Univariate analyses are analogous to the Durbin-Watson test for first-order serial pattern and bivariate analyses are analogous to Schoener's t^2/r^2 statistic (Solow 1989). Permutation versions of these two tests can be done. Options allow you to select the sequencing variable and to turn off multivariate commensuration.

Usage

sp(data, expon = 1, commens = TRUE, number.perms, exact = FALSE,
save.test,sequence,variables)

Arguments

data	an object of class matrix (or an object coercible by as.matrix) with columns representing response variables.
expon	allows selection of alternative exponents in distance calculations.
commens	a logical value indicating whether to perform multivariate commensuration.
number.perms	number of permutations used if a Monte Carlo resampling procedure is to be used.
exact	logical indicating whether to perform an exact test or use a Monte Carlo resampling procedure.
save.test	logical indicating whether to return Monte Carlo resampled test statistic values.
sequence	a numeric vector specifying how the data should be ordered for the analysis.
variables	a character string of the names to be used in the analysis. These should match names found in the data.frame.

Details

In this analysis of ungrouped data, the agreement measure (1 - average Euclidean distance between ordered observations/average Euclidean distance among all possible pairs of observations) is a statistic describing first-order serial dependency. Significance of the null hypothesis of no first-order serial dependency is provided by the Pearson Type III approximation on the first 3 exact moments of the permutation distribution by default, optionally by exact enumeration for small samples by specifying the exact option, or by a Monte Carlo resampling procedure by specifying the number.perms option.

Value

sp returns an object of class MRSPObj.

The functions summary as well as print can be used to obtain a summary of the test.

Generic accessor functions pvalue and ResampVals can be used to obtain the p-value and Monte Carlo resampled test statistic values respectively.

References

Solow, A.R. 1989. A randomization test for independence of animal locations. Ecology 70, 1546–1549.

See Also

MRSPObj

Examples

sp(blue162[,4:5], expon = 1,number.perms = 1000,save.test = TRUE)

Blossom documentation built on May 29, 2017, 10:55 p.m.