ttest: Perform bootstrap or Monte Carlo t-tests on the NRMSE...

In rclsp: A Modular Two-Step Convex Optimization Estimator for Ill-Posed Problems

Perform bootstrap or Monte Carlo t-tests on the NRMSE statistic from the CLSP estimator.

Description

This function either (a) resamples residuals via a nonparametric bootstrap to generate an empirical NRMSE sample, or (b) produces synthetic right-hand side vectors b from a user-defined or default distribution and re-estimates the model. It tests whether the observed NRMSE significantly deviates from the null distribution of resampled or simulated NRMSE values.

Usage

ttest(
  object,
  reset = FALSE,
  sample_size = 50L,
  seed = NULL,
  distribution = NULL,
  partial = FALSE,
  simulate = FALSE
)

Arguments

object	An object of class "clsp".
reset	Logical, default = FALSE. If TRUE, forces recomputation of the NRMSE null distribution.
sample_size	Integer, default = 50. Size of the Monte Carlo simulated sample under H0.
seed	Integer or NULL, default = NULL. Optional random seed to override the default.
distribution	Function or NULL, default = NULL. Distribution for generating synthetic b vectors. One of: rnorm, runif, or a custom RNG function. Defaults to standard normal.
partial	Logical, default = FALSE. If TRUE, runs the t-test on the partial NRMSE: during simulation, the C-block entries are preserved and the M-block entries are simulated.
simulate	Logical, default = FALSE. If TRUE, performs a parametric Monte Carlo simulation by generating synthetic right-hand side vectors b. If FALSE (default), executes a nonparametric bootstrap procedure on residuals without re-estimation.

Value

A named list containing test results and null distribution statistics:

p_one_left

P(nrmse \le null mean)

p_one_right

P(nrmse \ge null mean)

p_two_sided

2-sided t-test p-value

nrmse

Observed value

mean_null

Mean of null distribution

std_null

Standard deviation of null distribution

rclsp documentation built on Feb. 19, 2026, 5:07 p.m.