Propagate ACS uncertainty for a linear combination.

Propagate ACS uncertainty for a linear combination.

Usage

acs_linear(estimates, moes, weights, cov = NULL, conf = 0.9)

Arguments

estimates

Numeric estimates.

moes

Numeric MOEs corresponding to estimates.

weights

Numeric weights for the linear combination.

cov

Optional covariance matrix on the standard-error scale. A scalar is interpreted as a common off-diagonal covariance.

conf

Confidence level associated with input and output MOEs.

Value

A one-row data frame with estimate, moe, and se.

Details

A scalar cov is a covariance, not a correlation. In contrast, acs_aggregate(cov_strategy = "constant") accepts a scalar correlation because that interface derives covariances from group-specific MOEs.

Examples

acs_linear(c(100, 50, 25), c(10, 8, 6), weights = c(2, -1, 0.5))
#>   estimate      moe       se
#> 1    162.5 21.74856 13.22219