Concept

Autoregressive–moving-average model

Related publications (123)

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Bioclimatic conditions of the Lower Silesia region (South-West Poland) from 1966 to 2017

Paolo Perona

This work analyses the temporal and spatial characteristics of bioclimatic conditions in the Lower Silesia region. The daily time values (12UTC) of meteorological variables in the period 1966–2017 from seven synoptic stations of the Institute of Meteorolog ...

Springer2020

Simultaneous autoregressive models for spatial extremes

Emeric Rolland Georges Thibaud

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

WILEY2020

Functional lagged regression with sparse noisy observations

Victor Panaretos, Tomas Rubin

A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions. In practice, the underlying regressor curve time series are not always ...

WILEY2020

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

François Fleuret, Nikolaos Pappas, Angelos Katharopoulos, Apoorv Vyas

Transformers achieve remarkable performance in several tasks but due to their quadratic complexity, with respect to the input’s length, they are prohibitively slow for very long sequences. To address this limitation, we express the self-attention as a line ...

Idiap2020

Characterizing time intermittency in non-diffusive fast ion transport through plasma turbulence

Ambrogio Fasoli, Ivo Furno, Paolo Ricci, Marcelo Baquero Ruiz, Oulfa Chellaï, Fabian Manke

Turbulent fast ion transport has been investigated in astrophisycal, laboratory and fusion plasmas. When gyro- and drift-averaging across plasma structures manifest as non-markovian and non-local effects, this results in generally non-diffusive transport. ...

IOP PUBLISHING LTD2020

Dimensionality Reduction and Network Inference for Climate Data Using delta-MAPS: Application to the CESM Large Ensemble Sea Surface Temperature

Athanasios Nenes

A framework for analyzing and benchmarking climate model outputs is built upon delta-MAPS, a recently developed complex network analysis method. The framework allows for the possibility of highlighting quantifiable topological differences across data sets, ...

AMER GEOPHYSICAL UNION2019

Application of Time Series Methods on Long-Term Structural Monitoring Data for Fatigue Analysis

Eugen Brühwiler, Bartlomiej Wojciech Sawicki, Morteza Ahmadivala

Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...

2019

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Existing depth sensing techniques have many shortcomings in terms of resolution, completeness, and accuracy. The performance of 3-D broadcasting systems is therefore limited by the challenges of capturing high-resolution depth data. In this paper, we prese ...

IEEE2019

Constructed in 1969, the Chillon viaducts constitute a vital component of the Swiss roadway network. The bridge deck was strengthened in 2015 by means of an Ultra High Performance Fiber Reinforced Cement-based Composite for alleviating the effects of deter ...

2019

Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...

Elsevier2019