Results 61 to 70 of about 7,202 (166)
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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A Seasonal Transmuted Geometric INAR Process: Modeling and Applications in Count Time Series
MathematicsIn this paper, the authors introduce the transmuted geometric integer-valued autoregressive model with periodicity, designed specifically to analyze epidemiological and public health time series data. The model uses a transmuted geometric distribution as
Aishwarya Ghodake +4 more
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Investigation of the relationship between macro-economic variables and tax evasion using nonlinear approaches [PDF]
اقتصاد باثباتThe main purpose of present study is to investigate the relationship between macroeconomic variables and tax evasion using nonlinear approaches. . First of all, it was used Markov Switching Vector Autoregression method, statistics and information from ...
masoumeh motallebi, Mohammad Alizadeh
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Recursive Estimation of Autoregressions
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1989 SUMMARY This paper is concerned with the recursive estimation of autoregressive models, in particular the realtime determination of the order of such a specification. A model selection criterion based on the minimum description length principle due to Rissanen is discussed and strong consistency in the stationary situation is shown ...
Hannan, E. J. +2 more
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Materials ProceedingsThis research aims to develop an unsupervised machine learning technique for ball bearing fault detection and fault diagnosis. It evaluates vibration signals through Autoregression (AR) models and Fuzzy C-means (FCM) clustering for experimental data from
Rafey Mehmood Alam +2 more
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Inflation Forecasting: The Practice of Using Synthetic Procedures
Мир новой экономики, 2019 The article contains a review of inflation forecasting models, including the most popular class of models as one-factor models: random walk, direct autoregression, recursive autoregression, stochastic volatility with an unobserved component and of the ...
E. V. Balatskiy, M. A. Yurevich
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The Baltic countries sectoral share price indexes VAR model
Lietuvos Matematikos Rinkinys, 2011 According to the same modern Baltic countries economical and political integration, united OMX Baltic security market created.The main purpose of this article is to forecast her sectoral share price indexes according to their interdependent relationship ...
Roma Uzdanavičiūtė +1 more
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CoRR, 2013 We introduce a deep, generative autoencoder capable of learning hierarchies of distributed representations from data. Successive deep stochastic hidden layers are equipped with autoregressive connections, which enable the model to be sampled from quickly and exactly via ancestral sampling.
Karol Gregor +4 more
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Media Ekonomi dan Manajemen, 2018 This study purposed to identify overconfidence behavior investor in Indonesia Stock Exchange from 2014 until 2016. Overconfidence is a psychological bias that can cause investors to excessive trading as the effect of the belief that they have specific ...
Indri Hartiyaningsih, Yanuar Rachmansyah
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Transformation Autoregressive Networks
, 2018 The fundamental task of general density estimation $p(x)$ has been of keen interest to machine learning. In this work, we attempt to systematically characterize methods for density estimation. Broadly speaking, most of the existing methods can be categorized into either using: \textit{a}) autoregressive models to estimate the conditional factors of the
Junier B. Oliva +6 more
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