Results 31 to 40 of about 3,433,600 (309)
The formulation of structural time series models in discrete and continuous time [PDF]
, 1983 This paper sets out an approach for modelling univariate time series, including those in which observations are available on a daily basis. An underlying continuous time model is formulated and it is shown that this model has important implications for ...
Harvey, A. C., Harvey, Andrew C.
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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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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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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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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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Information theoretic results for stationary time series and the Gaussian-generalized von Mises time series [PDF]
, 2021 This chapter presents some novel information theoretic results for the analysis of stationary time series in frequency domain. In particular, the spectral distribution that corresponds to the most uncertain or unpredictable time series with some values ...
Gatto, Riccardo
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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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