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 NA s. |
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)