Results 31 to 40 of about 2,530,237 (313)
Polynomial Regressions and Nonsense Inference
Econometrics, 2013 Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples.
Daniel Ventosa-Santaulària +1 more
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Investor Sentiment Measurement and Time Series Analysis [PDF]
SHS Web of Conferences, 2023 Investor sentiment is one of the destabilizing factors in the stock market. In the past, some scholars have proposed models for the measurement of emotions. On this basis, this paper selects 9 factors (closed-end fund discount rate, trading volume of the
Bai Yuchen
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Eddies: Fluid Dynamical Niches or Transporters?–A Case Study in the Western Baltic Sea
Frontiers in Marine Science, 2019 Fluid flows in the ocean have a strong impact on the growth and distribution of planktonic communities. In this case study, we applied a Lagrangian eddy detection and tracking tool and a transfer operator approach to data from a coupled hydrodynamical ...
Rahel Vortmeyer-Kley +5 more
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On predicting climate under climate change
Environmental Research Letters, 2013 Can today’s global climate model ensembles characterize the 21st century climate in their own ‘model-worlds’? This question is at the heart of how we design and interpret climate model experiments for both science and policy support.
Joseph D Daron, David A Stainforth
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Nonlinear Analysis of Financial Time Series [PDF]
Ovidius University Annals: Economic Sciences Series, 2022 One of the axioms of the modern science states that, if one can identify an exact mathematical description of a physical system, then a very detailed understanding of the system’s properties is possible.
Sorin Vlad, Mariana Vlad
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Visibility Graph Based Time Series Analysis. [PDF]
PLoS ONE, 2015 Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead
Mutua Stephen, Changgui Gu, Huijie Yang
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Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Sensors, 2021 A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT).
Ricardo Petri Silva +3 more
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Wavelet analysis of covariance with application to atmospheric time series [PDF]
, 2000 Multiscale analysis of univariate time series has appeared in the literature at an ever increasing rate. Here we introduce the multiscale analysis of covariance between two time series using the discrete wavelet transform.
Whitcher, Brandon +2 more
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Time series data analysis under indeterminacy
Journal of Big Data, 2023 The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals or imprecise.
Muhammad Aslam
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A Machine-Learning Framework for Modeling and Predicting Monthly Streamflow Time Series
Hydrology, 2023 Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread.
Hatef Dastour, Quazi K. Hassan
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