One-to-one correspondences between discrete multivariate stationary, self-similar, and stationary increment fields

In this article, we consider three important classes of n-variate fields indexed by the set of N dimensional integers, namely stationary, stationary increment, and self-similar fields. We connect these classes through bijective transformations. The one-to-one correspondence between stationary and self-similar fields, where the index of self-similarity is a tuple of positive definite matrices, is given by a version of the Lamperti transformation. In addition, we introduce generalized AR(1) type equations, whose unique stationary solutions are obtained via these transformations. Last, we apply the transformations in order to construct multivariate stationary fractional Ornstein-Uhlenbeck fields of the first and second kind, including a brief simulation study of bivariate Ornstein-Uhlenbeck sheets.

Authors

Institutions

Publication Details

Journal
Stochastic Models
Published
2025-04-17
DOI
https://doi.org/10.1080/15326349.2025.2485116
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

One-to-one correspondences between discrete multivariate stationary, self-similar, and stationary increment fields

Marko Voutilainen, Ville Peltonen
Stochastic Models
Complex Systems and Time Series Analysis
article

One-to-one correspondences between discrete multivariate stationary, self-similar, and stationary increment fields

Marko Voutilainen, Ville Peltonen
article en

Abstract

In this article, we consider three important classes of n-variate fields indexed by the set of N dimensional integers, namely stationary, stationary increment, and self-similar fields. We connect these classes through bijective transformations. The one-to-one correspondence between stationary and self-similar fields, where the index of self-similarity is a tuple of positive definite matrices, is given by a version of the Lamperti transformation. In addition, we introduce generalized AR(1) type equations, whose unique stationary solutions are obtained via these transformations. Last, we apply the transformations in order to construct multivariate stationary fractional Ornstein-Uhlenbeck fields of the first and second kind, including a brief simulation study of bivariate Ornstein-Uhlenbeck sheets.

Stochastic ModelsVol. 41(4)
University of Turku (FI)
Reduced inequalities
Openalex Percentile: Top 88%
Complex Systems and Time Series Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

One-to-one correspondences between discrete multivariate stationary, self-similar, and stationary increment fields — Marko Voutilainen, Ville Peltonen · Stochastic Models (2025) | TGRS Research Map | TGRS