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A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning Ensemble Distributionally Robust Bayesian Optimisation The Proxy Presumption: From Semantic Embeddings to Valid Social Measures Modulated learning for private and distributed regression with just a single sample per client device Query-efficient model evaluation using cached responses Functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks Optimal Experiments for Partial Causal Effect Identification Order-Agnostic Autoregressive Modelling with Missing Data Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes Tuning Derivatives for Causal Fairness in Machine Learning Spherical Flows for Sampling Categorical Data Bayesian Rain Field Reconstruction using Commercial Microwave Links and Diffusion Model Priors GRALIS: A Unified Canonical Framework for Linear Attribution Methods via Riesz Representation Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning Jacobian-Velocity Bounds for Deployment Risk Under Covariate Drift Self-Attention as Transport: Limits of Symmetric Spectral Diagnostics Perturbation is All You Need for Extrapolating Language Models Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization Realizable Bayes-Consistency for General Metric Losses Graph Convolutional Support Vector Regression for Robust Spatiotemporal Forecasting of Urban Air Pollution Segmenting Human-LLM Co-authored Text via Change Point Detection Stochastic Schrödinger Diffusion Models for Pure-State Ensemble Generation Understanding Self-Supervised Learning via Latent Distribution Matching The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-modal Divergence Imbalanced Classification under Capacity Constraints On the Spectral Structure and Objective Equivalence of Orthogonal Multilabel Fisher Discriminants Partially Observed Structural Causal Models First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint Robust and Fast Training via Per-Sample Clipping
Marginal Persistence and Dynamic Copula Dependence in Sov...
[Submitted on 8 Apr 2026 (v1), last revised 31 Aug 2026 (this ve · 2026-04-09 · via stat updates on arXiv.org

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Abstract:This paper develops an observed-data likelihood for applying moving-aggregate modified autoregressive (MAGMAR) copula time-series models to discrete sovereign rating-migration counts with time-varying exposure. An annual count identifies a probability-integral-transform interval rather than a unique latent point, so the likelihood integrates the latent process over the complete sequence of count intervals. A guided sequential Monte Carlo implementation incorporates the parameter-dependent stationary marginal adjustment of MAGMAR directly inside this integration. In sovereign ratings from Fitch, Moody's, and S\&P over 1963--2025, the migration counts are strongly overdispersed relative to a binomial margin and, under an exposure-conditioned static beta-binomial margin, MAGMAR improves substantially on MAG. The interpretation changes once the marginal mean is allowed to depend on the lagged migration rate: residual serial correlation in the count margin disappears, a reference dynamic-margin fit gives only a small MAGMAR improvement, and information criteria favor MAG. Numerical profiles, higher-precision refits, and parameter-recovery experiments show that marginal persistence and copula persistence are only weakly separated in this short discrete series. The results therefore support interval integration as the correct observation layer while showing that conclusions about latent dynamic dependence must be conditioned on the specification of the count margin.

Submission history

From: Marina Palaisti Prof Dr [view email]
[v1] Wed, 8 Apr 2026 20:11:53 UTC (22 KB)
[v2] Mon, 31 Aug 2026 20:09:47 UTC (110 KB)