Synthesis from a saturated model based on all combinations of the predictor variables.
Synthesises one variable (y
) from all possible
combinations of its precitors (x
). A bootstrap sample is created
from the original values of y
within each unique combinations of
of xp
(the syntheisied values of the grouping variable).
syn.satcat(y, x, xp, proper = FALSE, ...)
y |
an original data vector of length |
x |
a matrix ( |
xp |
a matrix ( |
proper |
if |
... |
additional parameters. |
It is intended that the variables in x
are categorical (factor)
variables. If y
is also a categorical variable syn.satcat
will
give the same results as fitting a saturated polychotomous regression model but
will usually be much faster. syn.satcat
will fail with an error message
if previous syntheses have generated a combination of variables in xp
that was not present in x
. Use of the syn.catall
method for
grouped variables can overcome this.
A list with two components:
res |
a data frame of dimension |
fit |
the cross-tabulation of the original predictor variables. |
ods <- SD2011[, c("region", "sex", "agegr", "placesize")] s1 <- syn(ods, method = c("sample", "cart", "satcat", "cart")) ## Not run: ### mostly fails because too many small categories s2 <- syn(ods, method = c("sample", "cart", "cart", "satcat")) ## End(Not run)
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