confint.lgspline: Confidence Intervals for lgspline Coefficients

In lgspline: Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation

Confidence Intervals for lgspline Coefficients

Description

Wald-based confidence intervals for regression coefficients and, when available, correlation parameters (on the working scale).

Usage

## S3 method for class 'lgspline'
confint(object, parm, level = 0.95, ...)

Arguments

object	A fitted lgspline object with return_varcovmat = TRUE.
parm	Optional vector of parameter indices or names. Default returns all regression parameters; working-scale correlation parameters are appended when available.
level	Confidence level. Default 0.95.
...	Additional arguments passed to wald_univariate.

Details

For Gaussian identity-link models, t-distribution quantiles are used with effective degrees of freedom N - \mathrm{trace}(\mathbf{XUGX}^\top). All other families use normal quantiles.

Correlation parameter intervals (if VhalfInv_params_estimates and VhalfInv_params_vcov are present) are computed on the unbounded working scale via a Wald interval.

Value

A matrix with columns giving lower and upper confidence limits, named e.g. 2.5 % and 97.5 % for 95% intervals. When available, rows for working-scale correlation parameters are appended after the regression coefficients.

lgspline documentation built on Aug. 5, 2026, 1:10 a.m.