| xtabs {Matrix} | R Documentation |
Create a contingency table from cross-classifying factors, usually contained in a data frame, using a formula interface.
This is a fully compatible extension of the standard stats
package xtabs() function with the added option
to produce a sparse matrix result via sparse = TRUE.
xtabs(formula = ~., data = parent.frame(), subset, sparse = FALSE, na.action,
exclude = c(NA, NaN), drop.unused.levels = FALSE)
formula |
a formula object with the cross-classifying variables
(separated by +) on the right hand side (or an object which
can be coerced to a formula). Interactions are not allowed. On the
left hand side, one may optionally give a vector or a matrix of
counts; in the latter case, the columns are interpreted as
corresponding to the levels of a variable. This is useful if the
data have already been tabulated, see the examples below. |
data |
an optional matrix or data frame (or similar: see
model.frame) containing the variables in the
formula formula. By default the variables are taken from
environment(formula). |
subset |
an optional vector specifying a subset of observations to be used. |
sparse |
logical specifying if the result should be a sparse matrix, i.e., inheriting from sparseMatrix. Only works for two factors (since there are no higher-order sparse array classes yet). |
na.action |
a function which indicates what should happen when
the data contain NAs. |
exclude |
a vector of values to be excluded when forming the set of levels of the classifying factors. |
drop.unused.levels |
a logical indicating whether to drop unused
levels in the classifying factors. If this is FALSE and
there are unused levels, the table will contain zero marginals, and
a subsequent chi-squared test for independence of the factors will
not work. |
For (non-sparse) xtabs results,
there is a summary method for contingency table objects created
by table or xtabs, which gives basic information and
performs a chi-squared test for independence of factors (note that the
function chisq.test currently only handles 2-d tables).
If a left hand side is given in formula, its entries are simply
summed over the cells corresponding to the right hand side; this also
works if the lhs does not give counts.
By default, when sparse=FALSE,
a contingency table in array representation of S3 class c("xtabs",
"table"), with a "call" attribute storing the matched call.
When sparse=TRUE, a sparse numeric matrix, specifically an
object of S4 class dgTMatrix.
The stats package version xtabs and its
references.
## See for non-sparse examples:
example(xtabs, package = "stats")
## similar to "nlme"s 'ergoStool' :
d.ergo <- data.frame(Type = paste("T", rep(1:4, 9*4), sep=""),
Subj = gl(9,4, 36*4))
xtabs(~ Type + Subj, data=d.ergo) # 4 replicates each
set.seed(15) # a subset of cases:
xtabs(~ Type + Subj, data=d.ergo[sample(36, 10),], sparse=TRUE)
## Hypothetical two level setup:
inner <- factor(sample(letters[1:25], 100, replace = TRUE))
inout <- factor(sample(LETTERS[1:5], 25, replace = TRUE))
fr <- data.frame(inner = inner, outer = inout[as.integer(inner)])
xtabs(~ inner + outer, fr, sparse = TRUE)