arXiv (All)
open access
Reliability inference for semi-Markov models based on multiple trajectories
We develop nonparametric inference for reliability indicators of discrete-time semi-Markov systems from independent trajectories observed over a common fixed horizon. Augmenting the physical state by the backward recurrence time yields a finite coupled Markov representation on the observed age range
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Modeling the Effectiveness of Antibiotic Therapies Against Sepsis Using Continuous-time Hidden Markov Models#438532
- Discrete Wasserstein Flows for One-Step Generative Modeling#1156627
- Provably Tractable NFA-Constrained Language Generation via HMMs#1154450
- Projection, Degeneracy, and the Unitarity Formulation of the Black Hole Information Paradox: A Temporal Rate Ontology Analysis#716098
- Representation Transitions Reveal Predictive Structure in Complex Systems: A Trajectory-Level Reconstruction in a Critical System#798406
Record · ID 1013267
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive