most citedSVEMnet: An R package for Self-Validated Elastic-Net Ensembles and Multi-Response Optimization in Small-Sample Mixture-Process Experiments

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ME2026

Parameter-Specific Bias Diagnostics in Random-Effects Panel Data Models

Andrew T. Karl

The Hausman specification test assesses the random-effects specification by comparing the random-effects estimator with a fixed-effects alternative. This note shows how a recently…

stat.ME2026

Insights into the Relationship Between D- and A-optimal Designs

Andrew T. Karl, Bradley Jones

For a fixed linear-model basis, we show that the criterion factors into an inverse- scale term and a dimensionless sphericity factor that depends only on eigenvalue dispersi…

math.ST2026

Order-Induced Variance in the Moving-Range Sigma Estimator: A Total-Variance Decomposition

Andrew T. Karl

I--MR charts commonly estimate the process standard deviation via the span-2 average moving range divided by the unbiasing constant ; unlike the unbiased sample standard…

stat.CO2026

Motivating REML via Prediction-Error Covariances in EM Updates for Linear Mixed Models

Andrew T. Karl

We present a computational motivation for restricted maximum likelihood (REML) estimation in linear mixed models using an expectation--maximization (EM) algorithm. At each iteratio…

stat.CO20261 cited

SVEMnet: An R package for Self-Validated Elastic-Net Ensembles and Multi-Response Optimization in Small-Sample Mixture-Process Experiments

Andrew T. Karl

SVEMnet is an R package for fitting Self-Validated Ensemble Models (SVEM) with elastic-net base learners and performing multi-response optimization in small-sample mixture-process…

stat.ME2024

A Randomized Permutation Whole-Model Test Heuristic for Self-Validated Ensemble Models (SVEM)

Andrew T. Karl

We introduce a heuristic to test the significance of fit of Self-Validated Ensemble Models (SVEM) against the null hypothesis of a constant response. A SVEM model averages predicti…