Description Usage Arguments Details Value Author(s) See Also Examples
Compute summary statistics (sums, means) of data subsets.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | groupSums(object, ...)
## S4 method for signature 'matrix'
groupSums(object, MARGIN, by, na.rm = FALSE, ...)
## S4 method for signature 'sparseMatrix'
groupSums(object, MARGIN, by, na.rm = FALSE, ...)
## S4 method for signature 'Mefa'
groupSums(object, MARGIN, by, replace, na.rm = FALSE, ...)
groupMeans(object, ...)
## S4 method for signature 'matrix'
groupMeans(object, MARGIN, by, na.rm = FALSE, ...)
## S4 method for signature 'sparseMatrix'
groupMeans(object, MARGIN, by, na.rm = FALSE, ...)
## S4 method for signature 'Mefa'
groupMeans(object, MARGIN, by, replace, na.rm = FALSE, ...)
|
object |
an object. |
MARGIN |
numeric, |
by |
a vector of grouping elements corresponding to dimensions
of |
replace |
a data frame to be used when applying the method on a
|
na.rm |
logical. Should missing values be removed?
Sum is calculated by zeroing out |
... |
other argument, currently not implemented. |
The method sums/averages cells in a matrix.
The functions behind these methods use sparse matrices,
so calculations can be more efficient compared to using
aggregate
.
An object similar to the input one.
Peter Solymos <solymos@ualberta.ca>
rowSums
, rowMeans
,
colSums
, colMeans
Standard aggregate
in package stats
aggregate.mefa
in package
mefa for S3 "mefa"
objects.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | x <- data.frame(
sample = paste("Sample", c(1,1,2,2,3,4), sep="."),
species = c(paste("Species", c(1,1,1,2,3), sep="."),
"zero.pseudo"), count = c(1,2,10,3,4,0))
samp <- data.frame(samples=levels(x$sample), var1=1:2)
taxa <- data.frame(specnames=levels(x$species), var2=c("b","a"))
rownames(samp) <- samp$samples
rownames(taxa) <- taxa$specnames
x2 <- Xtab(count ~ sample + species, x, cdrop=FALSE,rdrop=TRUE)
x5 <- Mefa(x2, samp, taxa, join="inner")
groupSums(as.matrix(x2), 1, c(1,1,2))
groupSums(as.matrix(x2), 2, c(1,1,2,2))
groupSums(x2, 1, c(1,1,2))
groupSums(x2, 2, c(1,1,2,2))
groupSums(x5, 1, c(1,1,2))
groupSums(x5, 2, c(1,1,2,2))
groupMeans(as.matrix(x2), 1, c(1,1,2))
groupMeans(as.matrix(x2), 2, c(1,1,2,2))
groupMeans(x2, 1, c(1,1,2))
groupMeans(x2, 2, c(1,1,2,2))
groupMeans(x5, 1, c(1,1,2))
groupMeans(x5, 2, c(1,1,2,2))
|
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