A two-sample test for subspace equality in networks uses the Frobenius norm of projection matrix differences, with proven asymptotic normality to Gaussian under logarithmic average degree growth.
Journal of Computational and Graphical Statistics , pages =
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4representative citing papers
The zero-divisor graph Γ(Q) of a poset Q with 0 is complemented if and only if Q is quasi-complemented, with complemented and uniquely complemented graphs coinciding for any such poset.
FAMM approximates full MM-estimation via weighted least squares to speed up outlier-robust model selection while preserving performance and satisfying consistency conditions.
A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.
citing papers explorer
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Two-Sample Hypothesis Testing for Subspace Equality in Network Data
A two-sample test for subspace equality in networks uses the Frobenius norm of projection matrix differences, with proven asymptotic normality to Gaussian under logarithmic average degree growth.
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Complemented zero-divisor graph of posets
The zero-divisor graph Γ(Q) of a poset Q with 0 is complemented if and only if Q is quasi-complemented, with complemented and uniquely complemented graphs coinciding for any such poset.
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Fast Approximate MM-Estimation for Outlier Robust Model Selection
FAMM approximates full MM-estimation via weighted least squares to speed up outlier-robust model selection while preserving performance and satisfying consistency conditions.
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A Mixed Self-Exciting Process to Model Epileptic Seizures
A Bayesian mixed Hawkes process with Weibull baseline intensity and random effects is developed to model seizure clustering and heterogeneity in focal epilepsy from the Human Epilepsy Project data.