Results 11 to 20 of about 40,844,823 (304)
Fractional integration and cointegration in US financial time series data [PDF]
, 2011 This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets ...
Gil-Alana, Luis A. +5 more
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Estimation of missing data in a geophysical series of precipitation
, 2021 The analysis of dynamic systems is a topic of great interest in the basic sciences since it allows direct inference of the behavior of different systems. The study of physical phenomena provides large databases that, if recorded at regular time intervals,
GALLARDO PÉREZ, HENRY DE JESÚS +5 more
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Time Series Data Cleaning: A Survey
IEEE Access, 2020 Errors are prevalent in time series data, which is particularly common in the industrial field. Data with errors could not be stored in the database, which results in the loss of data assets.
Xi Wang, Chen Wang
doaj +1 more source
Causal learning with interrupted time series data
Judgment and Decision Making, 2023 People often test changes to see if the change is producing the desired result (e.g., does taking an antidepressant improve my mood, or does keeping to a consistent schedule reduce a child’s tantrums?).
Yiwen Zhang, Benjamin M. Rottman
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Review of Deep Learning Applied to Time Series Prediction [PDF]
Jisuanji kexue yu tansuo, 2023 The time series is generally a set of random variables that are observed and collected at a certain frequency in the course of something??s development.
LIANG Hongtao, LIU Shuo, DU Junwei, HU Qiang, YU Xu
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A Family of Correlated Observations: From Independent to Strongly Interrelated Ones
Stats, 2020 This paper proposes a new classification of correlated data types based upon the relative number of direct connections among observations, producing a family of correlated observations embracing seven categories, one whose empirical counterpart currently
Daniel A. Griffith
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Generalized Network Autoregressive Processes and the GNAR Package
Journal of Statistical Software, 2020 This article introduces the GNAR package, which fits, predicts, and simulates from a powerful new class of generalized network autoregressive processes.
Marina Knight +3 more
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Time Series Data Mining for Sport Data: a Review
International Journal of Computer Science in Sport, 2022 Time series data mining deals with extracting useful and meaningful information from time series data. Recently, the increasing use of temporal data, in particular time series data, has received much attention in the literature. Since most of sports data
Komitova Rumena +3 more
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Time series clustering of COVID-19 pandemic-related data
Data Science and Management, 2023 The COVID-19 pandemic continues to impact daily life worldwide. It would be helpful and valuable if we could obtain valid information from the COVID-19 pandemic sequential data itself for characterizing the pandemic.
Zhixue Luo, Lin Zhang, Na Liu, Ye Wu
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Bermuda Atlantic Time-Series Study (BATS) Sediment Trap - Flux
, 2023 <p>This dataset is published on Zenodo by the Simons CMAP curators for long-term care. All credits go to the data producers at the Bermuda Atlantic Time-series Study (BATS): https://bats.bios.asu.edu/bats-data/ </p><p>The BATS ...
Simons CMAP +1 more
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