Computes approximate Wald confidence intervals for selected parameters from a fitted Gaussian AD model.
Arguments
- fit
A fitted model object returned by
fit_gau.- level
Confidence level between 0 and 1.
- parameters
Which parameters to include:
"all"(default),"mu","phi", or"sigma".
Value
An object of class gau_ci, a list with elements
settings, level, mu, phi, and sigma.
Each non-NULL element is a data frame with columns param,
est, se, lower, upper, and level.
Details
This helper currently supports complete-data Gaussian AD fits.
Standard errors are based on large-sample approximations:
\(SE(\hat{\mu}_t) \approx \hat{\sigma}_t / \sqrt{n}\)
\(SE(\hat{\sigma}_t) \approx \hat{\sigma}_t / \sqrt{2n}\)
\(SE(\hat{\phi}) \approx \sqrt{(1-\hat{\phi}^2)/n}\) for free \(\phi\) entries
Examples
if (FALSE) { # \dontrun{
y <- simulate_gau(n_subjects = 80, n_time = 6, order = 1, phi = 0.4)
fit <- fit_gau(y, order = 1)
ci <- ci_gau(fit)
ci$mu
ci$phi
ci$sigma
} # }