g
to
apply to each row of the data, and returns the expectation of g
under the
empirical distribution of the data. it also returns a confidence interval for
the expectation, and the number of samples used to compute the expectation.R/utils.R
expectation_data.Rd
example: expectation_data(D, function(x) (x-colMeans(D)) %*% t(x-colMeans(D))) computes the covariance of the data D, except the matrix structure is lost (it's just a vector, which can be coerced back to a matrix if needed).
expectation_data(
data,
g = function(x) x,
...,
compute_stats = TRUE,
alpha = 0.05
)
a matrix of data
a function to apply to each row of the data
additional arguments to pass to g
whether to compute CIs for the expectations
the confidence level for the confidence interval for each component of the expectation (if compute_stats is TRUE)
if compute_stats is TRUE, then a list with the following components: value - The estimate of the expectation ci - The confidence intervals for each component of the expectation n - The number of samples otherwise, just the value of the expectation.