arXiv (All)
open access
Modeling cyclostationarity in time series using ASCA
Modern data analysis across diverse disciplines increasingly relies on time series. Many of these datasets exhibit cyclostationarity, where patterns approximately repeat in a regular manner, often across multiple time scales, such as daily, weekly or yearly cycles. In this context, statistical infer
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
- Clustering of Time Series Data: Measures, Methods, and Applications#492525
- Clustered Local Projections for Short and Ultra-Short Time Series -- A Hierarchical Bayesian Framework#615145
- Clustered Local Projections for Short and Ultra-Short Time Series -- A Hierarchical Bayesian Framework#614178
- gasmodel: An R Package for Generalized Autoregressive Score Models#924396
- gasmodel: An R Package for Generalized Autoregressive Score Models#920165
Record · ID 1076826
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