ci_gau: Confidence intervals for fitted Gaussian AD models

In antedep: Antedependence Models for Longitudinal Data

Confidence intervals for fitted Gaussian AD models

Description

Computes approximate Wald confidence intervals for selected parameters from a fitted Gaussian AD model.

Usage

ci_gau(fit, level = 0.95, parameters = "all")

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".

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

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.

See Also

fit_gau, ci_cat, ci_inad

Examples

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

antedep documentation built on April 25, 2026, 1:06 a.m.