Results 21 to 30 of about 3,433,600 (309)
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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Ocean/Atmosphere Time Series Analysis [PDF]
, 2022 This package contains all necessary files for the course Ocean/Atmosphere Time Series Analysis, an introduction to data and time series analysis for graduate students in oceanography, atmospheric science, and climate. This material is generally taught
Jonathan M. Lilly
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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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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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Demonstrating the value of larger ensembles in forecasting physical systems
Tellus: Series A, Dynamic Meteorology and Oceanography, 2016 Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying ...
Reason L. Machete, Leonard A. Smith
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findstructureintime/Time-Series-Analysis v0.0.1 [PDF]
, 2020 This is the github repository containing the four Matlab code modules with sample examples introduced in the paper, Finding Structure in Time: Visualizing and Analyzing Behavioral Time ...
Tian Linger Xu
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Explainable Time Series Tree: An Explainable Top-Down Time Series Segmentation Framework
IEEE Access, 2023 A wide range of Machine Learning algorithms can model time series to address classification, forecasting, and clustering problems. However, time series may exhibit characteristics that complicate these tasks, such as repeating patterns and seasonal ...
Vitor de Castro Silva +3 more
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Mixed portmanteau tests for time-series models [PDF]
, 2005 This paper obtains the joint limiting distribution of residuals and squared residuals of a general time-series model. Based on this, we propose a mixed portmanteau statistic for testing the adequacy of fitted time-series models.
Wong, H +3 more
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