pith:3VVYQYWK
ARMA approximation of a Non-separable Spatio-Temporal Model with Fractional Smoothnesses in Space and Time
Rational approximations in time turn a non-separable fractional spatio-temporal model into a convergent vector ARMA process.
arxiv:2604.26535 v2 · 2026-04-29 · stat.ME · cs.NA · math.NA
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\pithnumber{3VVYQYWKG5AANTV5KRAFHAXSFF}
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Claims
We propose a discretization method based on rational approximations in time to handle arbitrary smoothnesses, which leads to a vector autoregressive moving average process (VARMA). We prove that the covariance function of the approximation converges pointwise, determine explicit convergence rates as a function of spatial and temporal resolutions and the accuracy of the rational approximation.
The rational approximation of the temporal fractional operator can be made arbitrarily accurate while preserving the non-separable structure and validity of the resulting spatio-temporal covariance without introducing uncontrolled bias.
Rational approximations in time convert a fractional space-time SPDE into a convergent VARMA model that handles arbitrary smoothness and improves forecasting when temporal smoothness is correctly specified.
Receipt and verification
| First computed | 2026-06-08T01:04:05.893239Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
dd6b8862ca374006cebd54405382f229723bc34057a3fd5e3ccd004dc3ab64a5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3VVYQYWKG5AANTV5KRAFHAXSFF \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: dd6b8862ca374006cebd54405382f229723bc34057a3fd5e3ccd004dc3ab64a5
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
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