Perform a test for conditional independence between the first two variables in the data set, given the remaining variables.
ci_test(lg_object, h = function(x) x^2, S = function(y) rep(T,
nrow(y)), n_rep = 500, nodes = 100, M = NULL, M_sim = 1500,
M_corr = 1.5, n_corr = 1.2, extend = 0.3, return_time = TRUE)An object of type lg, as produced by the
lg_main-function
The h-function used in the calculation of the test statistic.
The default value is h(x) = x^2.
The integration area in the test statistic. Logical function that takes grid points as argument.
The number of replicated bootstrap samples
Either the number of equidistant nodes to generate, or a vector of nodes supplied by the user
The value for M in the accept-reject algorithm if already known
The number of replicates to simulate in order to find a value for M
Correction factor for M, to be on the safe side
Correction factor for n_new, so that we mostly will generate enough observations in the first go
How far to extend the grid beyond the extreme data points when interpolating, in share of the range
Measure how long the test takes to run, and return along with the test result