arXiv (All)
open access
A Non-Stationary Spatio-Temporal Covariance Model with Dynamic Advection Effects for Rainfall Data
We propose a non-stationary model constructed using a mixture of spatio-temporal covariance models with advection effects; namely, models that have larger covariance values along an orientation vector in the spatio-temporal index set, that simulate wind direction and cloud movement. We show that a m
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
- Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model#1274570
- Regimes of precipitation change over Europe and the Mediterranean#1219681
- A Dynamic Likelihood Approach to Filtering for Advection-Diffusion Dynamics#677328
- A Dynamic Likelihood Approach to Filtering for Advection-Diffusion Dynamics#674131
- Inference for segregation indices in the presence of spatial autocorrelation#202714
Record · ID 1326333
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