Results 21 to 30 of about 103,352 (315)

Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances [PDF]

Journal of Applied Econometrics, 2016
SummaryWe propose a new class of models specifically tailored for spatiotemporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, that is, SARAR(1, 1), by exploiting the recent advancements in score‐driven (SD) models typically used in time series econometrics.
Leopoldo Catania, Anna Gloria Billé
openaire   +4 more sources

Forecasting the development of electricity from renewable energy sources in Poland against the background of the European Union countries

Economics and Environment, 2023
One of the key elements in the development of countries is energy stability particularly related to ensuring, among other things, continuity of power supply.
Marcin Stanuch, Krzysztof Adam Firlej
doaj   +1 more source

Limitations of Autoregressive Models and Their Alternatives [PDF]

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
NAACL 2021 (same content, more relaxed layout)
Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner   +4 more
openaire   +2 more sources

Learned Lossless Image Compression With Combined Channel-Conditioning Models and Autoregressive Modules

IEEE Access, 2023
Lossless image compression is an important research field in image compression. Recently, learning-based lossless image compression methods achieved impressive performance compared with traditional lossless methods, such as WebP, JPEG2000, and FLIF.
Ran Wang, Jinming Liu, Heming Sun, Jiro Katto   +3 more
doaj   +1 more source

Track Prediction for HF Radar Vessels Submerged in Strong Clutter Based on MSCNN Fusion with GRU-AM and AR Model

Remote Sensing, 2021
High-frequency (HF) surface-wave radar has a wide range of applications in marine monitoring due to its long-distance, wide-area, and all-weather detection ability.
Ling Zhang, Jingzhi Zhang, Jiong Niu, Q. M. Jonathan Wu, Gangsheng Li   +4 more
doaj   +1 more source

A Novel Method of Adaptive Kalman Filter for Heading Estimation Based on an Autoregressive Model

Applied Sciences, 2019
With the popularity of smartphones and the development of microelectromechanical system (MEMS), the pedestrian dead reckoning (PDR) algorithm based on the built-in sensors of a smartphone has attracted much research.
Dashuai Chai, Guoliang Chen, Shengli Wang   +2 more
doaj   +1 more source

A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue

Sensors, 2022
Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and ...
Giovanni Corvini, Silvia Conforto
doaj   +1 more source

A Modified Weighted Symmetric Estimator for a Gaussian First-order Autoregressive Model with Additive Outliers

Walailak Journal of Science and Technology, 2012
Guttman and Tiao [1], and Chang [2] showed that the effect of outliers may cause serious bias in estimating autocorrelations, partial correlations, and autoregressive moving average parameters (cited in Chang et al. [3]).
Wararit PANICHKITKOSOLKUL
doaj   +1 more source

Butterworth-Induced Autoregressive Model

Mathematics
This work proposes a novel autoregressive (AR) modeling framework in which the model structure and coefficients are induced from the analytical properties of Butterworth filters.
Carlos Brás-Geraldes, J. Leonel Rocha, Filipe Martins   +2 more
doaj   +1 more source

Bitcoin and the South Sea Company: A comparative analysis

Revista Finanzas y Política Económica, 2021
This paper examines historical Bitcoin price data together with the price data of a well-known and generally accepted historical asset price bubble (the 1720 South Sea Bubble) with the aim of identifying possible similarities.
Michael Demmler, Amilcar Orlian Fernández Domínguez   +1 more
doaj   +1 more source