-
1
-
-
0034288490
-
The theta model: a decomposition approach to forecasting
-
Assimakopoulos, V., Nikolopoulos, K., The theta model: a decomposition approach to forecasting. Int. J. Forecast. 16:4 (2000), 521–530.
-
(2000)
Int. J. Forecast.
, vol.16
, Issue.4
, pp. 521-530
-
-
Assimakopoulos, V.1
Nikolopoulos, K.2
-
2
-
-
33745943643
-
Spyros makridakis: an interview with the international journal of forecasting
-
Fildes, R., Nikolopoulos, K., Spyros makridakis: an interview with the international journal of forecasting. Int. J. Forecast. 22:3 (2006), 625–636.
-
(2006)
Int. J. Forecast.
, vol.22
, Issue.3
, pp. 625-636
-
-
Fildes, R.1
Nikolopoulos, K.2
-
3
-
-
84973545775
-
Models for optimising the theta method and their relationship to state space models
-
Fioruci, J.A., Pellegrini, T.R., Louzada, F., Petropoulos, F., Koehler, A., Models for optimising the theta method and their relationship to state space models. Int. J. Forecast. 32:4 (2016), 1151–1161.
-
(2016)
Int. J. Forecast.
, vol.32
, Issue.4
, pp. 1151-1161
-
-
Fioruci, J.A.1
Pellegrini, T.R.2
Louzada, F.3
Petropoulos, F.4
Koehler, A.5
-
4
-
-
84960378176
-
The relationship between model complexity and forecasting performance for computer intelligence optimization in finance
-
Ghandara, A., Michalewicz, Z., Zurbruegge, R., The relationship between model complexity and forecasting performance for computer intelligence optimization in finance. Int. J. Forecast. 32:3 (2016), 598–613.
-
(2016)
Int. J. Forecast.
, vol.32
, Issue.3
, pp. 598-613
-
-
Ghandara, A.1
Michalewicz, Z.2
Zurbruegge, R.3
-
5
-
-
0003428336
-
Applied Nonparametric Regression
-
Cambridge University Press Cambridge
-
Härdle, W., Applied Nonparametric Regression. 1992, Cambridge University Press, Cambridge.
-
(1992)
-
-
Härdle, W.1
-
6
-
-
0003413187
-
Neural Networks: A Comprehensive Foundation
-
Pearson US
-
Haykin, S., Neural Networks: A Comprehensive Foundation. 1998, Pearson, US.
-
(1998)
-
-
Haykin, S.1
-
7
-
-
67650246505
-
Neural Networks and Learning Machines
-
Prentice Hall US
-
Haykin, S., Neural Networks and Learning Machines. 2008, Prentice Hall, US.
-
(2008)
-
-
Haykin, S.1
-
8
-
-
84890882829
-
Introduction to the Math of Neural Networks
-
Heaton Research, Inc
-
Heaton, J., Introduction to the Math of Neural Networks. 2012, Heaton Research, Inc.
-
(2012)
-
-
Heaton, J.1
-
9
-
-
14844288728
-
The M3 competition: statistical tests of the results
-
Koning, A.J., Franses, P.H., Hibon, M., Stekler, H.O., The M3 competition: statistical tests of the results. Int. J. Forecast. 21:3 (2005), 397–409, 10.1016/j.ijforecast.2004.10.003.
-
(2005)
Int. J. Forecast.
, vol.21
, Issue.3
, pp. 397-409
-
-
Koning, A.J.1
Franses, P.H.2
Hibon, M.3
Stekler, H.O.4
-
10
-
-
84984426556
-
The accuracy of extrapolation (time series) methods: results of a forecasting competition
-
Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E., Winkler, R., The accuracy of extrapolation (time series) methods: results of a forecasting competition. J. Forecast. 1:2 (1982), 111–153, 10.1002/for.3980010202.
-
(1982)
J. Forecast.
, vol.1
, Issue.2
, pp. 111-153
-
-
Makridakis, S.1
Andersen, A.2
Carbone, R.3
Fildes, R.4
Hibon, M.5
Lewandowski, R.6
Newton, J.7
Parzen, E.8
Winkler, R.9
-
11
-
-
38249002551
-
The M-2 competition: a real-time judgmentally based forecasting study
-
Makridakis, S., Chatfield, C., Hibon, M., Lawrence, M., Mills, T., Ord, K., Simmons, L.F., The M-2 competition: a real-time judgmentally based forecasting study. Int. J. Forecast. 9 (1993), 5–23.
-
(1993)
Int. J. Forecast.
, vol.9
, pp. 5-23
-
-
Makridakis, S.1
Chatfield, C.2
Hibon, M.3
Lawrence, M.4
Mills, T.5
Ord, K.6
Simmons, L.F.7
-
12
-
-
0034288942
-
The M3-competition: results, conclusions and implications
-
Makridakis, S., Hibon, M., The M3-competition: results, conclusions and implications. Int. J. Forecast. 16:4 (2000), 451–476.
-
(2000)
Int. J. Forecast.
, vol.16
, Issue.4
, pp. 451-476
-
-
Makridakis, S.1
Hibon, M.2
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