Results 11 to 20 of about 56,489 (266)
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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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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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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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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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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