المؤلفون: Oelrich, Oscar, Villani, Mattias, 1973, Ankargren, Sebastian

المصدر: Journal of Forecasting. :103-117

مصطلحات موضوعية: Bayesian predictive synthesis, combining forecasts, density forecasts, macroeconomic forecasting, nonparametric methods

وصف الملف: print

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-221729Test
https://doi.org/10.1002/for.3030Test

المؤلفون: Ali, Hyder

المساهمون: Garrett, Ian, Taylor, Alex

مصطلحات موضوعية: Variance-covariance, Model Uncertainty, Equity Premium Prediction, Parameter Instability, Machine Learning, Dynamic Model Selection, Conditional CAPM, Combining Forecasts

الوصول الحر: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.873842Test

المؤلفون: João B. Assunção, Pedro Afonso Fernandes

المصدر: Forecasting, Vol 4, Iss 3, Pp 717-731 (2022)

مصطلحات موضوعية: time series, macroeconomic forecasting, nowcasting, error correction models, combining forecasts, Science (General), Q1-390, Mathematics, QA1-939

وصف الملف: electronic resource

العلاقة: https://www.mdpi.com/2571-9394/4/3/39Test; https://doaj.org/toc/2571-9394Test

الوصول الحر: https://doaj.org/article/76e88c92ebcb419f8825bd36d53a31cbTest

المؤلفون: Tommaso Di Fonzo, Daniele Girolimetto

المساهمون: DI FONZO, Tommaso, Girolimetto, Daniele

مصطلحات موضوعية: Linearly constrained multiple time series, Combining forecasts, Heuristic techniques, Evaluating forecasts, GDP from Income and Expenditure side

وصف الملف: STAMPA

العلاقة: info:eu-repo/semantics/altIdentifier/wos/WOS:000904903100003; volume:39; issue:1; firstpage:39; lastpage:57; numberofpages:19; journal:INTERNATIONAL JOURNAL OF FORECASTING; https://hdl.handle.net/11577/3403190Test; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85116330679; https://www.sciencedirect.com/science/article/pii/S0169207021001266Test

الإتاحة: https://doi.org/10.1016/j.ijforecast.2021.08.004Test
https://hdl.handle.net/11577/3403190Test
https://www.sciencedirect.com/science/article/pii/S0169207021001266Test

المؤلفون: Mohammad Raquibul Hossain, Mohd Tahir Ismail, Samsul Ariffin Bin Abdul Karim

المصدر: IEEE Access, Vol 9, Pp 132319-132328 (2021)

مصطلحات موضوعية: EMD, combining forecasts, time-series analytics, ARIMA, EWMA, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

العلاقة: https://ieeexplore.ieee.org/document/9546774Test/; https://doaj.org/toc/2169-3536Test

الوصول الحر: https://doaj.org/article/ed4181138f8944ba883f0ba517e28494Test

المؤلفون: Assunção, João B., Fernandes, Pedro Afonso

المصدر: Assunção , J B & Fernandes , P A 2022 , ' Nowcasting GDP : an application to Portugal ' , Forecasting , vol. 4 , no. 3 , pp. 717-731 . https://doi.org/10.3390/forecast4030039Test

مصطلحات موضوعية: Combining forecasts, Error correction models, Macroeconomic forecasting, Nowcasting, Time series

وصف الملف: application/pdf

العلاقة: https://ciencia.ucp.pt/en/publications/5301c9cb-a346-4aba-a26a-06d9bc8923abTest

الإتاحة: https://doi.org/10.3390/forecast4030039Test
https://ciencia.ucp.pt/en/publications/5301c9cb-a346-4aba-a26a-06d9bc8923abTest
https://ciencia.ucp.pt/ws/files/91464172/50202131.pdfTest
http://www.scopus.com/inward/record.url?scp=85164476407&partnerID=8YFLogxKTest
http://hdl.handle.net/10400.14/38631Test

المؤلفون: Georgia Papacharalampous (4399993), Hristos Tyralis (3795271)

مصطلحات موضوعية: Applied Computer Science, Hydrology, Statistics, Water Resources Engineering, Applied Statistics, Stochastic Analysis and Modelling, ARFIMA, combining forecasts, complex exponential smoothing, computer science, environmental informatics, exponential smoothing, forecast combinations, forecasting, geoscience, global-scale hydrology, hydroinformatics, hydrological forecasting, hydrological time series forecasting, large-sample hydrology, machine learning, Prophet, river flow, rivers, simple combinations, simple exponential smoothing, statistical hydrology, statistical learning, stochastic hydrology, stochastic model

العلاقة: https://figshare.com/articles/presentation/Simple_combinations_for_hydrological_time_series_forecasting/16821007Test

الإتاحة: https://doi.org/10.6084/m9.figshare.16821007.v1Test

المؤلفون: Georgia Papacharalampous (4399993), Hristos Tyralis (3795271)

مصطلحات موضوعية: Environmental Science, Applied Computer Science, Hydrology, Statistics, Water Resources Engineering, Applied Statistics, Stochastic Analysis and Modelling, ARFIMA, autocorrelation, climatic regime, combining forecasts, complex exponential smoothing, computer science, entropy, environmental informatics, exponential smoothing, feature extraction, forecast combintations, forecasting, geoscience, global-scale hydrology, hydroclimatic change, hydroclimatic feature, hydroclimatic regime, hydroclimatic signature, hydroclimatic time series, hydroclimatic variability, hydroinformatics, hydrological forecasting, hydrological science

العلاقة: https://figshare.com/articles/presentation/Characterization_of_annual_river_flow_time_series_and_interpretation_of_the_relative_performance_of_time_series_forecasting_methods/16821037Test

الإتاحة: https://doi.org/10.6084/m9.figshare.16821037.v1Test

المؤلفون: Georgia Papacharalampous (4399993), Hristos Tyralis (3795271)

مصطلحات موضوعية: Environmental Science, Applied Computer Science, Hydrology, Statistics, Water Resources Engineering, Applied Statistics, Stochastic Analysis and Modelling, Conceptual Modelling, ARFIMA, ARIMA, artificial intelligence, artificial neural networks, autocorrelation, automatic forecasting, benchmarking, big data, big data hydrology, catchment hydrology, climatic regime, combining forecasts, combining probabilistic forecasts, complex exponential smoothing, computer science, conceptual model, generalization, generalized random forests, geoscience, global-scale hydrology, gradient boosting machine, ensemble learning

العلاقة: https://figshare.com/articles/presentation/Machine_learning_concepts_and_methods_for_hydrological_post-processing_and_forecasting_invited_/16879438Test

الإتاحة: https://doi.org/10.6084/m9.figshare.16879438.v1Test

المؤلفون: Silva, Juliana C., Figueiredo, Manuel, Braga, A. C.

المساهمون: Universidade do Minho

مصطلحات موضوعية: ARIMA, Combining forecasts, Exponential smoothing, Forecasting demand, Science & Technology

وصف الملف: application/pdf

العلاقة: Silva J.C., Figueiredo M.C., Braga A.C. (2019) Demand Forecasting: A Case Study in the Food Industry. In: Misra S. et al. (eds) Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science, vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_5Test; 9783030243012; 0302-9743

الإتاحة: http://hdl.handle.net/1822/70503Test