Results 1 to 10 of about 1,135 (106)
Capturing asymmetry in COVID-19 counts using an improved skewness measure for time series data [PDF]
MethodsX, 2023 Capturing asymmetry among time series is an important area of research as it provides a range of information regarding the behaviour and distribution of the underlying series, which in turn proves to be useful for prediction.
Sudeep R. Bapat
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Data analysis-based time series forecast for managing household electricity consumption
Demonstratio Mathematica, 2022 Recently, electricity consumption forecasting has attracted much research due to its importance in our daily life as well as in economic activities. This process is seen as one of the ways to manage future electricity needs, including anticipating the ...
Bezzar Nour El-Houda +3 more
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A statistical study of COVID-19 pandemic in Egypt
Demonstratio Mathematica, 2021 The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19 ...
Radwan Taha
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Time series with infinite-order partial copula dependence
Dependence Modeling, 2022 Stationary and ergodic time series can be constructed using an s-vine decomposition based on sets of bivariate copula functions. The extension of such processes to infinite copula sequences is considered and shown to yield a rich class of models that ...
Bladt Martin, McNeil Alexander J.
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Open Mathematics, 2021 In this paper, we consider a novel estimation for partial functional linear regression models. The functional principal component analysis method is employed to estimate the slope function and the functional predictive variable, respectively.
Cao Peng, Sun Jun
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Detecting departures from meta-ellipticity for multivariate stationary time series
Dependence Modeling, 2021 A test for detecting departures from meta-ellipticity for multivariate stationary time series is proposed. The large sample behavior of the test statistic is shown to depend in a complicated way on the underlying copula as well as on the serial ...
Bücher Axel, Jaser Miriam, Min Aleksey
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Geometric fractional Brownian motion model for commodity market simulation
Alexandria Engineering Journal, 2021 The geometric Brownian motion (GBM) model is a mathematical model that has been used to model asset price paths. By incorporating Hurst parameter to GBM to characterize long-memory phenomenon, the geometric fractional Brownian motion (GFBM) model was ...
Siti Nur Iqmal Ibrahim +2 more
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Majalah Ilmiah Matematika dan Statistika, 2022 Forecasting is a technique for estimating a value on a particular object in the future by paying attention to past data. This forecasting uses the Exponential Smoothing models because the data used is in accordance with the model.
Muhammad Marizal, Fikha Mutiarani
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A unified perspective on some autocorrelation measures in different fields: A note
Open Mathematics, 2023 Using notions from linear algebraic graph theory, this article provides a unified perspective on some autocorrelation measures in different fields. They are as follows: (a) Orcutt’s first serial correlation coefficient, (b) Anderson’s first circular ...
Yamada Hiroshi
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Testing for explosive bubbles: a review
Dependence Modeling, 2023 This review discusses methods of testing for explosive bubbles in time series. A large number of recently developed testing methods under various assumptions about innovation of errors are covered.
Skrobotov Anton
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