Parallel quantile, median, mean
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)
prob |
A single probability at which to calculate the quantile. See |
dataList |
A list of numeric vectors or arrays, all of the same length and dimensions, over which to calculate “parallel” quantiles. |
weights |
Optional vector of the same length as |
... |
Numeric arguments. All arguments must have the same dimensions. See details. |
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.
pquantile, pquantile.fromList |
A vector or array containing quantiles. |
pmean, pmean.fromList |
A vector or array containing means. |
pmedian |
A vector or array containing medians. |
pminWhich.fromList |
A list with two components: |
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.
Peter Langfelder and Steve Horvath
# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.