Results 11 to 20 of about 103,352 (315)
Autoregressive conditional root model. [PDF]
, 2001 In this paper we develop a time series model which allows long-term disequilibriums to have epochs of non-stationarity, giving the impression that long term relationships between economic variables have temporarily broken down, before they endogenously collapse back towards their long term relationship.
Anders Rahbek, Neil Shephard
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AR, CR and ARCR modeling for simulations and analyses of karst groundwater quality parameters [PDF]
Geološki Anali Balkanskoga Poluostrva, 2018 Although an invisible component of the hydrologic cycle, groundwater generally takes precedence over other water resources in the area of drinking water supply.
Ristić-Vakanjac Vesna +4 more
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Random autoregressive models: A structured overview [PDF]
Econometric Reviews, 2021 41 pages, 1 figure, 1 ...
de Andrade Serra, P.J. +2 more
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Applied Sciences, 2023 With the recent expansion of social media in the form of social networks, online portals, and microblogs, users have generated a vast number of opinions, reviews, ratings, and feedback.
Roop Ranjan +7 more
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Applied Sciences, 2023 We present an any-to-one voice conversion (VC) system, using an autoregressive model and LPCNet vocoder, aimed at enhancing the converted speech in terms of naturalness, intelligibility, and speaker similarity.
Kadria Ezzine +2 more
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On a Mixture Autoregressive Model
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-workers to the mixture autoregressive (MAR) model for the modelling of non-linear time series. The models consist of a mixture of K stationary or non-stationary AR components. The advantages of the MAR model over the GMTD model include
Wong, CS, Li, WK
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Overview of Identification Methods of Autoregressive Model in Presence of Additive Noise
Mathematics, 2023 This paper presents an overview of the main methods used to identify autoregressive models with additive noises. The classification of identification methods is given. For each group of methods, advantages and disadvantages are indicated.
Dmitriy Ivanov, Zaineb Yakoub
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Spatial Temporal Conditional Auto-Regressive Model: A New Autoregressive Matrix
Austrian Journal of Statistics, 2016 In the study of geographical patterns of disease, multivariate areal data models proposed so far in the literature (Ma and Carlin, 2007; Carlin and Banerjee, 2003; Knorr-Held and Best, 2001) have allowed to handle several features of a phenomenon at the ...
Leonardo Mariella, Marco Tarantino
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Connection Science, 2023 This research aims to derive the average run length (ARL) evaluation of the double exponentially weighted moving average (double EWMA) control chart for observation data that follows exponential white noise in a time series model with an autoregressive ...
Kotchaporn Karoon +2 more
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Autoregressive functions estimation in nonlinear bifurcating autoregressive models [PDF]
Statistical Inference for Stochastic Processes, 2016 Bifurcating autoregressive processes, which can be seen as an adaptation of au-toregressive processes for a binary tree structure, have been extensively studied during the last decade in a parametric context. In this work we do not specify any a priori form for the two autoregressive functions and we use nonparametric techniques.
Bitseki Penda, Siméon Valère +1 more
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