Results 11 to 20 of about 10,039,445 (243)
Implementation of quasi-static time series simulations for analysis of the impact of electric vehicles on the grid [PDF]
, 2019 © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Allenspach, Cyril Armand +4 more
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Efficient Bayesian inference for natural time series using ARFIMA processes [PDF]
Nonlinear Processes in Geophysics, 2015 Many geophysical quantities, such as atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long memory (LM). LM implies that these quantities experience non-trivial temporal memory, which potentially not only enhances ...
T. Graves +3 more
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Bootstraping financial time series [PDF]
, 2002 It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations ...
Pascual, Lorenzo, Ruiz Ortega, Esther
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A Parametric Factor Model of the Term Structure of Mortality
Econometrics, 2019 The prototypical Lee–Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper, we propose a parametric factor model for the term structure of mortality where multiple factors are
Niels Haldrup +1 more
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Frontiers in Physics, 2021 Time irreversibility of a time series, which can be defined as the variance of properties under the time-reversal transformation, is a cardinal property of non-equilibrium systems and is associated with predictability in the study of financial time ...
Ryutaro Mori, Ruiyun Liu, Yu Chen
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Language Time Series Analysis [PDF]
, 2006 We use the Detrended Fluctuation Analysis (DFA) and the Grassberger-Proccacia analysis (GP) methods in order to study language characteristics. Despite that we construct our signals using only word lengths or word frequencies, excluding in this way huge ...
Abrams +41 more
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Entropy, 2021 Time series consist of data observed sequentially in time, and they are assumed to stem from an underlying stochastic process [...]
Christian H. Weiß
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Denoising Deterministic Time Series [PDF]
, 2006 This paper is concerned with the problem of recovering a finite, deterministic time series from observations that are corrupted by additive, independent noise. A distinctive feature of this problem is that the available data exhibit long-range dependence
Lalley, Steven P., Nobel, Andrew B.
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Entropy, 2023 Time series are sequentially observed data in which important information about the phenomenon under consideration is contained not only in the individual observations themselves, but also in the way these observations follow one another [...]
Christian H. Weiß
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Mandelbrot's Stochastic Time Series Models
Earth and Space Science, 2019 I survey and illustrate the main time series models that Mandelbrot introduced into time series analysis in the 1960s and 1970s. I focus particularly on the members of the additive fractional stable family including Lévy flights and fractional Brownian ...
N. W. Watkins
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