Performs a bootstrap hypothesis test using the supplied statistic.
The stdx parameter is used to define an empirical distribution that satisfies the null hypothesis.
boot_calib(x, stdx, stat, B, ...)A list of
pval the p-value from the test
t0 the statistic for the observations x
nullt The statistic evaluated on the resamples
stdx The stdx passed into boot_calib()
B The number of resamples requested
nullt_messages Any error messages for the corresponding resample
The returned object has a bespoke class TFORGE for easy use of print().
Symmetric matrix observations. Either a fsm or a kfsm.
Either a fsm or kfsm of matrices transformed to satisfy the null hypothesis OR sampling weights for each matrix in x for weighted bootstrap calibration (sampling weights should be optimised and also generate an empirical distribution that satisfies the null hypothesis).
Function to compute the statistic.
The number of bootstrap samples to use.
Passed to stat
The function stat is applied to x and all resamples, with the result returned in the t0 and nullt elements of the returned object, respectively.
Errors in evaluating stat on resamples are recorded in the nullt_messages and lead to NA values for the statistic in the nullt element of the returned object.
The p-value is the fraction of non-NA resample statistic values that are greater than stat applied to x.