For each dimension computes a t-based CI: mean ± t(α/2, n-1) × (SD / sqrt(n)) where α = 1 - conf_level.

lq_group_ci(points, conf_level = 0.95)

Arguments

points

Numeric matrix (units x dims) — one row per unit in the group

conf_level

Confidence level (default 0.95)

Value

Numeric matrix (n_dims x 3): columns are [mean, ci_lower, ci_upper]. When nrow(points) == 1 the CI bounds are ±Inf.