Description Usage Arguments Value Author(s) References See Also Examples
A tool for determining the number of significant clusters produced using hclust() with the assumption of no a priori groups.
1 2 3 4 5 6 |
data |
Input data in a matrix. |
num.expected |
The number of similarity profiles to generate for creating the expected distribution of the data. This value should be large. |
num.simulated |
The number of similarity profiles to generate for use in comparing the observed test statistic with its null distribution. This value should be large. |
method.cluster |
The method of clustering to use with
|
method.distance |
This value should be either an option to pass
to the function |
method.transform |
An option to specify a transform, if any, to
be applied to the data. Possible values are |
alpha |
The alpha level at which to reject the null hypothesis. If the null is rejected, the test continues and tests each sub-tree recursively until either all subtrees are exhausted by reaching the individual level or there are no significant distance. Due to the nature of multiple testing inherent in this process, care should be taken when choosing this alpha level. |
sample.orientation |
The orientation of the data, either |
const |
The value of the constant to be used in adjusting the
Bray-Curtis Dissimilarity coefficient, if any is to be used. Any
positive value of |
silent |
A logical value indicating whether anything should be
printed during the code execution. If |
increment |
An integer value indicating, if |
undef.zero |
A logical value indicating whether undefined values arising from a
denominator equal to 0 in the Bray-Curtis/Czekanowski Dissimilarity Indices should result
in |
warn.braycurtis |
A logical value indicating whether a warning should be printed
when using the |
A list object is produced with the following components:
numgroups |
The number of groups which are found to be statistically significant. |
significantclusters |
A list of length numgroups with each element containing the sample IDs (row/column numbers in the corresponding original data) that are in each significant cluster. |
pval |
The merge component from the hclust results with an extra column of p-values. These p-values are for testing whether the two groups in that row are statistically different. |
hclust |
An object of class hclust which is just the results of running hclust on the original data. |
Douglas Whitaker and Mary Christman
Clarke, K.R., Somerfield, P.J., and Gorley, R.N., 2008. Testing of null hypotheses in exploratory community analyses similarity profiles and biota-environment linkage. J. Exp. Mar. Biol. Ecol. 366, 56–69.
Yoshioka, P.M., 2008. Misidentification of the Bray-Curtis similarity index. Mar. Ecol. Prog. Ser. 368, 309–310.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## Not run:
# Load the USArrests dataset included with R
# And use abbreviations of state names
# We leave out the third column because
# it is on a different scale
usarrests<-USArrests[,c(1,2,4)]
rownames(usarrests)<-state.abb
# Run simprof on the data
res <- simprof(data=usarrests,
method.distance="braycurtis")
# Graph the result
pl.color <- simprof.plot(res)
## End(Not run)
|
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