Results 41 to 50 of about 7,202 (166)
ANALYSIS AND FORECASTING THE DYNAMICS OF ADVERTISING BOTS ACTIVITY
Вестник университета, 2020 When introducing a new product or service to the market, a manufacturer or retailer is faced with the need to develop a promotion strategy. Taking into account the recent trends in e-commerce and social media marketing, it makes sense to evaluate the ...
Yu. V. Trushina +3 more
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Reports on Geodesy and GeoinformaticsThis study presents a short-term forecast of UT1-UTC and LOD using two methods, i.e. Dynamic Mode Decomposition (DMD) and combination of Least-Squares and Vector Autoregression (LS+VAR).
Michalczak Maciej, Ligas Marcin
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ZOTMPo–INAR(1) Process: Entropy and Modeling of Epidemiological Count Time Series Data
EntropyIn this article, we propose a first-order integer-valued autoregressive (INAR(1)) model based on binomial thinning, in which the innovation sequence follows a zero–one–two-modified Poisson (ZOTMPo) distribution.
Manik Awale +5 more
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Nonlinear network autoregression
The Annals of Statistics, 2023 We study general nonlinear models for time series networks of integer and continuous valued data. The vector of high dimensional responses, measured on the nodes of a known network, is regressed non-linearly on its lagged value and on lagged values of the neighboring nodes by employing a smooth link function.
Mirko Armillotta, Konstantinos Fokianos
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FORECASTING OF THE STOCK RATE OF LEADING WORLD COMPANIES USING ECONOMETRIC METHODS AND DCF ANALYSIS
International Journal of Innovative Technologies in Economy, 2020 In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric ...
Olena Nikolaieva +2 more
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Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie ŚrodowiskaEngaging in investment activities plays a crucial and strategic role in fostering the growth of businesses and ensuring their resilience in the market.
Waldemar Wójcik +4 more
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On geometric recurrence for time-inhomogeneous autoregression
Modern Stochastics: Theory and Applications, 2023 The time-inhomogeneous autoregressive model AR(1) is studied, which is the process of the form ${X_{n+1}}={\alpha _{n}}{X_{n}}+{\varepsilon _{n}}$, where ${\alpha _{n}}$ are constants, and ${\varepsilon _{n}}$ are independent random variables. Conditions
Vitaliy Golomoziy
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CoRR, 2020 Autoregressive models use chain rule to define a joint probability distribution as a product of conditionals. These conditionals need to be normalized, imposing constraints on the functional families that can be used. To increase flexibility, we propose autoregressive conditional score models (AR-CSM) where we parameterize the joint distribution in ...
Chenlin Meng +4 more
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