Results 31 to 40 of about 10,097,276 (285)
Economics: Journal Articles, 2019 Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics.
Thompson Erica L., Smith Leonard A.
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Predictive analytics beyond time series: Predicting series of events extracted from time series data
Wind Energy, 2022 Realizing carbon neutral energy generation creates the challenge of accurately predicting time‐series generation data for long‐term capacity planning and for short‐term operational decisions.
Sambeet Mishra +3 more
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Assessing pricing assumptions for weather index insurance in a changing climate
Climate Risk Management, 2014 Weather index insurance is being offered to low-income farmers in developing countries as an alternative to traditional multi-peril crop insurance. There is widespread support for index insurance as a means of climate change adaptation but whether or not
J.D. Daron, D.A. Stainforth
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Real-Time Monitoring System for Shelf Life Estimation of Fruit and Vegetables
Sensors, 2020 The control of the main environmental factors that influence the quality of perishable products is one of the main challenges of the food industry.
Roque Torres-Sánchez +4 more
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CoRR, 2019 Multivariate time series is a very active topic in the research community and many machine learning tasks are being used in order to extract information from this type of data. However, in real-world problems data has missing values, which may difficult the application of machine learning techniques to extract information. In this paper we focus on the
Samuel Arcadinho, Paulo Mateus
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SSRN Electronic Journal, 2011 AbstractWe document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction.
Moskowitz, Tobias J. +2 more
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A Three-Stage Nonparametric Kernel-Based Time Series Model Based on Fuzzy Data
Mathematics, 2023 In this paper, a nonlinear time series model is developed for the case when the underlying time series data are reported by LR fuzzy numbers. To this end, we present a three-stage nonparametric kernel-based estimation procedure for the center as well as ...
Gholamreza Hesamian +2 more
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Time series momentum: Is it there?
Journal of Financial Economics, 2018 Time series momentum (TSM) refers to the predictability of the past 12-month return on the next one-month return and is the focus of several recent influential studies. This paper shows that asset-by-asset time series regressions reveal little evidence of TSM, both in- and out-of-sample. While the t-statistic in a pooled regression appears large, it is
HUANG, Dashan +3 more
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On predictability of time series [PDF]
Physica A: Statistical Mechanics and its Applications, 2019 The method to estimate the predictability of human mobility was proposed in [C. Song \emph{et al.}, Science {\bf 327}, 1018 (2010)], which is extensively followed in exploring the predictability of disparate time series. However, the ambiguous description in the original paper leads to some misunderstandings, including the inconsistent logarithm bases ...
Xu, Paiheng +3 more
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Time Series Compression Survey
ACM Computing Surveys, 2023 Smart objects are increasingly widespread and their ecosystem, also known as the Internet of Things (IoT), is relevant in many application scenarios. The huge amount of temporally annotated data produced by these smart devices demands efficient techniques for the transfer and storage of time series data.
Chiarot, Giacomo, Silvestri, Claudio
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