Perform an independence or a conditional independence test.
ci.test(x, y, z, data, test, ..., debug = FALSE)
An object of class htest containing the following components:
the value the test statistic.
the degrees of freedom of the approximate chi-squared or t distribution of the test statistic; the number of permutations computed by Monte Carlo tests. Semiparametric tests have both.
the p-value for the test.
a character string indicating the type of test performed, and whether Monte Carlo simulation or continuity correction was used.
a character string giving the name(s) of the data.
the value of the test statistic under the null hypothesis, always 0.
a character string describing the alternative hypothesis.
a character string (the name of a variable), a data frame, a numeric vector or a factor object.
a character string (the name of another variable), a numeric vector or a factor object.
a vector of character strings (the names of the conditioning
variables), a numeric vector, a factor object or a data frame. If
NULL an independence test will be executed.
a data frame containing the variables to be tested.
a character string, the label of the conditional independence
test to be used in the algorithm. If none is specified, the default test
statistic is the mutual information for categorical variables, the
Jonckheere-Terpstra test for ordered factors and the linear
correlation for continuous variables. See independence tests
for details.
optional arguments to be passed to the test specified by
test. See below for details.
a boolean value. If TRUE a lot of debugging output is
printed; otherwise the function is completely silent.
Marco Scutari
Additional arguments of the ci.test() function:
B: a positive integer, the number of permutations used to
compute the p-value of permutation tests. The default value is 5000
for nonparametric permutation tests and 100 for semiparametric
permutation tests.
fun: the function that computes the conditional independence
test in the custom-test test. fun must have arguments
x, y, z, data and args, in this order;
in other words, it must have signature function(x, y, z, data,
args). x and y will be the labels of the nodes to test for
independence (one character string each); z will be the labels of
the nodes in the conditioning set (a vector of character strings,
possibily NULL for empty sets); data will contain the
complete data set, with all the variables (a data frame); and args
will be a list containing any additional arguments to the test.
args: a list containing the optional arguments to fun,
for tuning custom-test test functions.
independence tests, arc.strength.
data(gaussian.test)
data(learning.test)
# using a data frame and column labels.
ci.test(x = "F" , y = "B", z = c("C", "D"), data = gaussian.test)
# using a data frame.
ci.test(gaussian.test)
# using factor objects.
attach(learning.test)
ci.test(x = F , y = B, z = data.frame(C, D))
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