Results 1 to 10 of about 9,146 (120)
Vector auto-regressive model (VAR) results’ versus auto-regressive distributive lags model (ARDL) results’ [PDF]
Maǧallaẗ Al-Buḥūṯ Al-Mālīyyaẗ wa Al-Tiğāriyyaẗ, 2021 The paper aims to test the possibility of getting the same results when applying two different econometric models in testing the relation between the development of financial sector and the economic growth in Egypt.
rania moawad
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Two-Threshold-Variable Integer-Valued Autoregressive Model
Mathematics, 2023 In the past, most threshold models considered a single threshold variable. However, for some practical applications, models with two threshold variables may be needed. In this paper, we propose a two-threshold-variable integer-valued autoregressive model
Jiayue Zhang, Fukang Zhu, Huaping Chen
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Autoregressive Diffusion Models
CoRR, 2021 We introduce Autoregressive Diffusion Models (ARDMs), a model class encompassing and generalizing order-agnostic autoregressive models (Uria et al., 2014) and absorbing discrete diffusion (Austin et al., 2021), which we show are special cases of ARDMs under mild assumptions. ARDMs are simple to implement and easy to train. Unlike standard ARMs, they do
Emiel Hoogeboom +5 more
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Variable Selection for the Spatial Autoregressive Model with Autoregressive Disturbances
Mathematics, 2021 Along with the rapid development of the geographic information system, high-dimensional spatial heterogeneous data has emerged bringing theoretical and computational challenges to statistical modeling and analysis.
Xuan Liu, Jianbao Chen
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Вестник Самарского университета: Естественнонаучная серия, 2023 For modeling in time series, models with fractional differences are widely used. The best known model is the ARFIMA (autoregressive fractionally integrated moving average) model.
Dmitriy V. Ivanov
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Saturation in autoregressive models [PDF]
Notas Económicas, 2006 In this paper, we extend the impulse saturation algorithm to a class of dynamic models. We show that the procedure is still correctly sized for stationary AR(1) processes, independently of the number of splits used for sample partitions. We derive theoretical power when there is an additive outlier in the data, and present simulation evidence showing ...
Carlos Santos, David Hendry
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Autoregressive optimal transport models
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023 Abstract Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the
Changbo Zhu, Hans-Georg Müller
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Multiscale autoregressive models and wavelets [PDF]
IEEE Transactions on Information Theory, 1999 The multiscale autoregressive (MAR) framework was introduced to support the development of optimal multiscale statistical signal processing. Its power resides in the fast and flexible algorithms to which it leads. While the MAR framework was originally motivated by wavelets, the link between these two worlds has been previously established only in the ...
Khalid Daoudi +2 more
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Forecasting domestic credit growth based on ARIMA model: Evidence from Vietnam and China [PDF]
Management Science Letters, 2019 Credit is an economic category and is also a product of the commodity economy, which exists through many socio-economic forms to promote economic growth. Therefore, the objective of this paper is to analyst, compare and forecast domestic credit growth in
Doan Van Dinh
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Seasonal functional autoregressive models [PDF]
Journal of Time Series Analysis, 2021 Functional autoregressive models are popular for functional time series analysis, but the standard formulation fails to address seasonal behaviour in functional time series data. To overcome this shortcoming, we introduce seasonal functional autoregressive time series models.
Atefeh Zamani +3 more
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