Nothing Special   »   [go: up one dir, main page]
create a website
FFORMPP: Feature-based forecast model performance prediction. (2022). Kang, Yanfei ; Li, Feng ; Talagala, Thiyanga S.
In: International Journal of Forecasting.
RePEc:eee:intfor:v:38:y:2022:i:3:p:920-943.

Full description at Econpapers || Download paper

Cited: 2

Citations received by this document

Cites: 43

References cited by this document

Cocites: 31

Documents which have cited the same bibliography

Coauthors: 0

Authors who have wrote about the same topic

Citations

Citations received by this document

  1. On the update frequency of univariate forecasting models. (2024). Petropoulos, Fotios ; Spiliotis, Evangelos.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:314:y:2024:i:1:p:111-121.

    Full description at Econpapers || Download paper

  2. Bayesian forecast combination using time-varying features. (2023). Li, Feng ; Kang, Yanfei.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:39:y:2023:i:3:p:1287-1302.

    Full description at Econpapers || Download paper

References

References cited by this document

  1. Adya, M. ; Armstrong, J.S. ; Collopy, F. ; Kennedy, M. An application of rule-based forecasting to a situation lacking domain knowledge. 2000 International Journal of Forecasting. 16 477-484

  2. Adya, M. ; Collopy, F. ; Armstrong, J.S. ; Kennedy, M. Automatic identification of time series features for rule-based forecasting. 2001 International Journal of Forecasting. 17 143-157

  3. Aiolfi, M. ; Timmermann, A. Persistence in forecasting performance and conditional combination strategies. 2006 Journal of Econometrics. 135 31-53

  4. Arinze, B. ; Kim, S.-L. ; Anandarajan, M. Combining and selecting forecasting models using rule based induction. 1997 Computers & Operations Research. 24 423-433
    Paper not yet in RePEc: Add citation now
  5. Cleveland, R.B. ; Cleveland, W.S. ; McRae, J.E. ; Terpenning, I. STL: a seasonal-trend decomposition procedure based on loess. 1990 Journal of Official Statistics. 6 3-73
    Paper not yet in RePEc: Add citation now

  6. Collopy, F. ; Armstrong, J.S. Rule-based forecasting: development and validation of an expert systems approach to combining time series extrapolations. 1992 Management Science. 38 1394-1414

  7. Hall, M. ; Frank, E. ; Holmes, G. ; Pfahringer, B. ; Reutemann, P. ; Witten, I.H. The WEKA data mining software: an update. 2009 ACM SIGKDD Explorations Newsletter. 11 10-18
    Paper not yet in RePEc: Add citation now

  8. Hyndman, R.J. ; Khandakar, Y. Automatic time series forecasting: the forecast package for R. 2008 Journal of Statistical Software. 26 1-22

  9. Hyndman, R.J. ; Koehler, A.B. Another look at measures of forecast accuracy. 2006 International Journal of Forecasting. 22 679-688

  10. Ingel, A. ; Shahroudi, N. ; Kängsepp, M. ; Tättar, A. ; Komisarenko, V. ; Kull, M. Correlated daily time series and forecasting in the M4 competition. 2020 International Journal of Forecasting. 36 121-128

  11. Kang, Y. ; Hyndman, R.J. ; Li, F. GRATIS: Generating time series with diverse and controllable characteristics. 2020 Statistical Analysis and Data Mining. 13 -
    Paper not yet in RePEc: Add citation now

  12. Kang, Y. ; Hyndman, R.J. ; Smith-Miles, K. Visualising forecasting algorithm performance using time series instance spaces. 2017 International Journal of Forecasting. 33 345-358

  13. Kourentzes, N. ; Barrow, D. ; Petropoulos, F. Another look at forecast selection and combination: Evidence from forecast pooling. 2019 International Journal of Production Economics. 209 226-235

  14. Kück, M., Crone, S. F., & Freitag, M. (2016). Meta-learning with neural networks and landmarking for forecasting model selection. In 2016 international joint conference on neural networks (IJCNN) (pp. 1499–1506).
    Paper not yet in RePEc: Add citation now
  15. Lemke, C. ; Gabrys, B. Meta-learning for time series forecasting and forecast combination. 2010 Neurocomputing. 73 2006-2016
    Paper not yet in RePEc: Add citation now

  16. Li, F. ; Villani, M. Efficient Bayesian multivariate surface regression. 2013 Scandinavian Journal of Statistics. 40 706-723

  17. Li, F. ; Villani, M. ; Kohn, R. Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densities. 2010 Journal of Statistical Planning and Inference. 140 3638-3654
    Paper not yet in RePEc: Add citation now
  18. Li, X. ; Kang, Y. ; Li, F. Forecasting with time series imaging. 2020 Expert Systems with Applications. 160 -
    Paper not yet in RePEc: Add citation now

  19. Lichtendahl Jr, K.C. ; Grushka-Cockayne, Y. ; Winkler, R.L. Is it better to average probabilities or quantiles?. 2013 Management Science. 59 1594-1611

  20. Maaten, L.v.d. ; Hinton, G. Visualizing data using t-SNE. 2008 Journal of Machine Learning Research. 9 2579-2605
    Paper not yet in RePEc: Add citation now

  21. Makridakis, S. ; Spiliotis, E. ; Assimakopoulos, V. The M4 competition: Results, findings, conclusion and way forward. 2018 International Journal of Forecasting. 34 802-808

  22. Matsypura, D. ; Thompson, R. ; Vasnev, A.L. Optimal selection of expert forecasts with integer programming. 2018 Omega. 78 165-175

  23. Meade, N. Evidence for the selection of forecasting methods. 2000 Journal of Forecasting. 19 515-535
    Paper not yet in RePEc: Add citation now
  24. Mersmann, O. Microbenchmark: Accurate timing functions. 2019 :
    Paper not yet in RePEc: Add citation now

  25. Montero-Manso, P. ; Athanasopoulos, G. ; Hyndman, R.J. ; Talagala, T.S. FFORMA: Feature-based forecast model averaging. 2020 International Journal of Forecasting. 36 86-92

  26. Petropoulos, F. ; Hyndman, R.J. ; Bergmeir, C. Exploring the sources of uncertainty: Why does bagging for time series forecasting work?. 2018 European Journal of Operational Research. 268 545-554

  27. Petropoulos, F. ; Makridakis, S. ; Assimakopoulos, V. ; Nikolopoulos, K. ‘Horses for courses’ in demand forecasting. 2014 European Journal of Operational Research. 237 152-163
    Paper not yet in RePEc: Add citation now

  28. Petropoulos, F. ; Svetunkov, I. A simple combination of univariate models. 2020 International Journal of Forecasting. 36 110-115

  29. Prudêncio, R. ; Ludermir, T. Using machine learning techniques to combine forecasting methods. 2004 En : Australasian joint conference on artificial intelligence. Springer:
    Paper not yet in RePEc: Add citation now
  30. Prudêncio, R.B. ; Ludermir, T.B. Meta-learning approaches to selecting time series models. 2004 Neurocomputing. 61 121-137
    Paper not yet in RePEc: Add citation now
  31. Rice, J.R. The algorithm selection problem. 1976 Advances in Computers. 15 65-118
    Paper not yet in RePEc: Add citation now

  32. Ruppert, D. ; Wand, M. ; Carroll, R. Semiparametric regression. 2003 Cambridge University Press: Cambridge

  33. Shah, C. Model selection in univariate time series forecasting using discriminant analysis. 1997 International Journal of Forecasting. 13 489-500

  34. Spiliotis, E. ; Kouloumos, A. ; Assimakopoulos, V. ; Makridakis, S. Are forecasting competitions data representative of the reality?. 2019 International Journal of Forecasting. -
    Paper not yet in RePEc: Add citation now

  35. Talagala, T.S. ; Hyndman, R.J. ; Athanasopoulos, G. Meta-learning how to forecast time series. 2018 Department of Econometrics & Business Statistics, Monash University:

  36. Tashman, L.J. Out-of-sample tests of forecasting accuracy: an analysis and review. 2000 International Journal of Forecasting. 16 437-450

  37. Tashman, L.J. ; Leach, M.L. Automatic forecasting software: A survey and evaluation. 2013 International Journal of Forecasting. 7 209-230
    Paper not yet in RePEc: Add citation now
  38. Venkatachalam, A. ; Sohl, J.E. An intelligent model selection and forecasting system. 1999 Journal of Forecasting. 18 167-180
    Paper not yet in RePEc: Add citation now

  39. Villani, M. ; Kohn, R. ; Giordani, P. Regression density estimation using smooth adaptive Gaussian mixtures. 2009 Journal of Econometrics. 153 155-173

  40. Wang, X. ; Kang, Y. ; Petropoulos, F. ; Li, F. The uncertainty estimation of feature-based forecast combinations. 2021 Journal of the Operational Research Society. -
    Paper not yet in RePEc: Add citation now
  41. Wang, X. ; Smith-Miles, K. ; Hyndman, R.J. Rule induction for forecasting method selection: meta-learning the characteristics of univariate time series. 2009 Neurocomputing. 72 2581-2594
    Paper not yet in RePEc: Add citation now
  42. Wang, X. ; Smith, K. ; Hyndman, R. Characteristic-based clustering for time series data. 2006 Data Mining and Knowledge Discovery. 13 335-364
    Paper not yet in RePEc: Add citation now
  43. Widodo, A., & Budi, I. (2013). Model selection using dimensionality reduction of time series characteristics. In International symposium on forecasting, Seoul, South Korea.
    Paper not yet in RePEc: Add citation now

Cocites

Documents in RePEc which have cited the same bibliography

  1. Forecast Selection and Representativeness. (2023). Siemsen, Enno ; Petropoulos, Fotios.
    In: Management Science.
    RePEc:inm:ormnsc:v:69:y:2023:i:5:p:2672-2690.

    Full description at Econpapers || Download paper

  2. FFORMPP: Feature-based forecast model performance prediction. (2022). Kang, Yanfei ; Li, Feng ; Talagala, Thiyanga S.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:38:y:2022:i:3:p:920-943.

    Full description at Econpapers || Download paper

  3. .

    Full description at Econpapers || Download paper

  4. Chiller Load Forecasting Using Hyper-Gaussian Nets. (2021). Satue, Manuel G ; Ortega, Manuel G ; Arahal, Manuel R.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2021:i:12:p:3479-:d:573553.

    Full description at Econpapers || Download paper

  5. Déjà vu: A data-centric forecasting approach through time series cross-similarity. (2021). Assimakopoulos, Vassilios ; Li, Feng ; Athiniotis, Nikolaos ; Petropoulos, Fotios ; Spiliotis, Evangelos ; Kang, Yanfei.
    In: Journal of Business Research.
    RePEc:eee:jbrese:v:132:y:2021:i:c:p:719-731.

    Full description at Econpapers || Download paper

  6. Forecasting in social settings: The state of the art. (2020). Petropoulos, Fotios ; Hyndman, Rob J ; Makridakis, Spyros.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:1:p:15-28.

    Full description at Econpapers || Download paper

  7. Time Series Forecasting in Stock Trading Markets: The Turning Point Curiosity. (2019). Lusk, Edward J.
    In: International Journal of Research in Business and Social Science (2147-4478).
    RePEc:rbs:ijbrss:v:8:y:2019:i:4:p:01-16.

    Full description at Econpapers || Download paper

  8. Feature-based Forecast-Model Performance Prediction. (2019). Kang, Yanfei ; Li, Feng ; Talagala, Thiyanga S.
    In: Monash Econometrics and Business Statistics Working Papers.
    RePEc:msh:ebswps:2019-21.

    Full description at Econpapers || Download paper

  9. Brain imaging and forecasting: Insights from judgmental model selection. (2019). Petropoulos, Fotios ; Wang, Xun ; Han, Weiwei.
    In: Omega.
    RePEc:eee:jomega:v:87:y:2019:i:c:p:1-9.

    Full description at Econpapers || Download paper

  10. Integrating human judgement into quantitative forecasting methods: A review. (2019). Siemsen, Enno ; Reisi, Mohsen ; Fahimnia, Behnam ; Arvan, Meysam .
    In: Omega.
    RePEc:eee:jomega:v:86:y:2019:i:c:p:237-252.

    Full description at Econpapers || Download paper

  11. Meta-learning how to forecast time series. (2018). Talagala, Thiyanga ; Hyndman, Rob ; Athanasopoulos, George.
    In: Monash Econometrics and Business Statistics Working Papers.
    RePEc:msh:ebswps:2018-6.

    Full description at Econpapers || Download paper

  12. Rule-based autoregressive moving average models for forecasting load on special days: A case study for France. (2018). Arora, Siddharth ; Taylor, James W.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:266:y:2018:i:1:p:259-268.

    Full description at Econpapers || Download paper

  13. Automating Analytics: Forecasting Time Series in Economics and Business. (2016). Gerunov, Anton.
    In: MPRA Paper.
    RePEc:pra:mprapa:71010.

    Full description at Econpapers || Download paper

  14. Automating Analytics: Forecasting Time Series in Economics and Business. (2016). Gerunov, Anton.
    In: Journal of Economics and Political Economy.
    RePEc:ksp:journ1:v:3:y:2016:i:2:p:340-349.

    Full description at Econpapers || Download paper

  15. Simple versus complex selection rules for forecasting many time series. (2015). Petropoulos, Fotios ; Fildes, Robert.
    In: Journal of Business Research.
    RePEc:eee:jbrese:v:68:y:2015:i:8:p:1692-1701.

    Full description at Econpapers || Download paper

  16. Wind speed forecasting using a portfolio of forecasters. (2014). Medina, Aurelio ; Pea, Rafael ; Graff, Mario ; Escalante, Hugo Jair .
    In: Renewable Energy.
    RePEc:eee:renene:v:68:y:2014:i:c:p:550-559.

    Full description at Econpapers || Download paper

  17. ‘Horses for Courses’ in demand forecasting. (2014). Nikolopoulos, Konstantinos ; Petropoulos, Fotios ; Assimakopoulos, Vassilios ; Makridakis, Spyros.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:237:y:2014:i:1:p:152-163.

    Full description at Econpapers || Download paper

  18. An evaluation of simple forecasting model selection rules. (2013). Petropoulos, Fotios ; Fildes, Robert.
    In: MPRA Paper.
    RePEc:pra:mprapa:51772.

    Full description at Econpapers || Download paper

  19. Essential econometric methods of forecasting agricultural commodity prices. (2013). Klimkowski, Cezary ; Grudkowska, Sylwia ; Stako, Stanisaw ; Gdek, Stanisaw ; Hamulczuk, Mariusz.
    In: Multiannual Program Reports.
    RePEc:ags:iafepr:164834.

    Full description at Econpapers || Download paper

  20. Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction. (2011). Nikolopoulos, Konstantinos ; Crone, Sven F. ; Hibon, Michele .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:27:y::i:3:p:635-660.

    Full description at Econpapers || Download paper

  21. Optimal forecasting model selection and data characteristics. (2007). Madden, Gary ; Fildes, Robert ; Tan, Joachim .
    In: Applied Financial Economics.
    RePEc:taf:apfiec:v:17:y:2007:i:15:p:1251-1264.

    Full description at Econpapers || Download paper

  22. Optimal forecasting model selection and data characteristics. (2007). Madden, Gary ; Fildes, Robert ; Tan, Joachim .
    In: MPRA Paper.
    RePEc:pra:mprapa:10819.

    Full description at Econpapers || Download paper

  23. Exponential smoothing: The state of the art--Part II. (2006). Gardner, Everette Jr., .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:22:y:2006:i:4:p:637-666.

    Full description at Econpapers || Download paper

  24. Findings from evidence-based forecasting: Methods for reducing forecast error. (2006). Armstrong, J..
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:22:y:2006:i:3:p:583-598.

    Full description at Econpapers || Download paper

  25. Forecasting for Environmental Decision Making. (2005). Armstrong, J..
    In: General Economics and Teaching.
    RePEc:wpa:wuwpgt:0502017.

    Full description at Econpapers || Download paper

  26. A short and mean-term automatic forecasting system--application to textile logistics. (2005). Castelain, Jean Marie ; Thomassey, Sebastien ; Happiette, Michel.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:161:y:2005:i:1:p:275-284.

    Full description at Econpapers || Download paper

  27. Forecasting for Environmental Decision Making. (2004). Armstrong, J..
    In: General Economics and Teaching.
    RePEc:wpa:wuwpgt:0412023.

    Full description at Econpapers || Download paper

  28. Smooth transition exponential smoothing. (2004). Taylor, James W..
    In: Journal of Forecasting.
    RePEc:jof:jforec:v:23:y:2004:i:6:p:385-404.

    Full description at Econpapers || Download paper

  29. The efficacy of using judgmental versus quantitative forecasting methods in practice. (2003). Manrodt, Karl B. ; Sanders, Nada R..
    In: Omega.
    RePEc:eee:jomega:v:31:y:2003:i:6:p:511-522.

    Full description at Econpapers || Download paper

  30. Automatic identification of time series features for rule-based forecasting. (2001). Armstrong, J. ; Adya, Monica ; Collopy, Fred ; Kennedy, Miles .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:17:y:2001:i:2:p:143-157.

    Full description at Econpapers || Download paper

  31. An application of rule-based forecasting to a situation lacking domain knowledge. (2000). Armstrong, J. ; Adya, Monica ; Collopy, Fred ; Kennedy, Miles .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:16:y:2000:i:4:p:477-484.

    Full description at Econpapers || Download paper

Coauthors

Authors registered in RePEc who have wrote about the same topic

Report date: 2025-01-02 00:53:28 || Missing content? Let us know

CitEc is a RePEc service, providing citation data for Economics since 2001. Sponsored by INOMICS. Last updated October, 6 2023. Contact: CitEc Team.