
Calculation of ``parallel'' quantiles, minima, maxima, medians, and means, across given arguments or across lists
pquantile(prob, ...)
pquantile.fromList(dataList, prob)
pmedian(...)
pmean(..., weights = NULL)
pmean.fromList(dataList, weights = NULL)
pminWhich.fromList(dataList)
A vector or array containing quantiles.
A vector or array containing means.
A vector or array containing medians.
A list with two components: min
gives the minima, which
gives the
indices of the elements that are the minima.
Dimensions are copied from dimensions of the input arguments.
If any of the input variables have dimnames
, the first non-NULL dimnames are copied into the output.
A single probability at which to calculate the quantile. See quantile
.
A list of numeric vectors or arrays, all of the same length and dimensions, over which to calculate ``parallel'' quantiles.
Optional vector of the same length as dataList
, giving the weights to be used in the
weighted mean. If not given, unit weights will be used.
Numeric arguments. All arguments must have the same dimensions. See details.
Peter Langfelder and Steve Horvath
Given numeric arguments, say x,y,z, of equal dimensions (and length), the pquantile
calculates and returns the quantile of the first components of x,y,z, then the second components, etc.
Similarly, pmedian
and pmean
calculate the median and mean, respectively.
The funtion pquantile.fromList
is identical to pquantile
except that the argument
dataList
replaces the ... in holding the numeric vectors over which to calculate the quantiles.
# Generate 2 simple matrices
a = matrix(c(1:12), 3, 4);
b = a+ 1;
c = a + 2;
# Set the colnames on matrix a
colnames(a) = spaste("col_", c(1:4));
# Example use
pquantile(prob = 0.5, a, b, c)
pmean(a,b,c)
pmedian(a,b,c)
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