A causality-based feature selection approach for multivariate time series forecasting, DBKDA, pp.97-102, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01467523
Testing for causality, Journal of Economic Dynamics and Control, vol.2, pp.329-352, 1980. ,
On Periodicity in Series of Related Terms, Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, vol.131, issue.818, pp.518-532, 1931. ,
The Analysis of Multiple Stationary Time Series, Journal of the Royal Statistical Society. Series B (Methodological), vol.15, issue.1, pp.125-139, 1953. ,
Chapter 10 Forecasting with Many Predictors, Handbook of Economic Forecasting, vol.1, pp.515-554, 2006. ,
, Generalized Shrinkage Methods for Forecasting Using Many Predictors, Journal of Business & Economic Statistics, vol.30, issue.4, pp.481-493, 2012.
Macroeconomic forecasting for Australia using a large number of predictors, 2017. ,
Forecasting daily stock market return using dimensionality reduction, Expert Systems with Applications, vol.67, pp.126-139, 2017. ,
Principal Component Analysis and Factor Analysis," in Principal Component Analysis, ser. Springer Series in Statistics, pp.115-128, 1986. ,
Nonlinear Component Analysis as a Kernel Eigenvalue Problem, Neural Computation, vol.10, issue.5, pp.1299-1319, 1998. ,
The dynamic factor analysis of economic time series, Latent Variables in Socio-Economic Models, 1977. ,
Forecasting Using Principal Components From a Large Number of Predictors, Journal of the American Statistical Association, vol.97, issue.460, pp.1167-1179, 2002. ,
Dynamic Factor Models, Oxford Handbook on Economic Forecasting, 2011. ,
Regression Shrinkage and Selection Via the Lasso, Journal of the Royal Statistical Society, Series B, vol.58, pp.267-288, 1994. ,
Ridge Regression: Biased Estimation for Nonorthogonal Problems, Technometrics, vol.12, issue.1, pp.55-67, 1970. ,
Forecasting US inflation by Bayesian model averaging, Journal of Forecasting, vol.28, issue.2, pp.131-144, 2009. ,
Forecasting large datasets with Bayesian reduced rank multivariate models, Journal of Applied Econometrics, vol.26, issue.5, pp.735-761, 2011. ,
Hierarchical shrinkage priors for dynamic regressions with many predictors, International Journal of Forecasting, vol.29, issue.1, pp.43-59, 2013. ,
Hybrid Intelligent Systems for Stock Market Analysis, Computational Science -ICCS, pp.337-345, 2001. ,
Feature subset selection on multivariate time series with extremely large spatial features, Data Mining Workshops, 2006. ICDM Workshops, pp.337-342, 2006. ,
Correlation and instance based feature selection for electricity load forecasting, Knowledge-Based Systems, vol.82, pp.29-40, 2015. ,
Box and Jenkins: Time Series Analysis, Forecasting and Control," in A Very British Affair, ser. Palgrave Advanced Texts in Econometrics, pp.161-215, 2013. ,
The analysis of multiple time-series, 1957. ,
Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models, Econometrica, vol.59, issue.6, pp.1551-1580, 1991. ,
Comparing backpropagation with a genetic algorithm for neural network training, Omega, vol.27, issue.6, pp.679-684, 1999. ,
A Comparison of BA, GA, PSO, BP and LM for Training Feed forward Neural Networks in e-Learning Context, International Journal of Intelligent Systems and Applications, vol.4, issue.7, pp.23-29 ,
The Var-NN Model for Multivariate Time Series Forecasting, vol.8, pp.35-43, 2008. ,
Comparison of Prediction Performances of Artificial Neural Network (ANN) and Vector Autoregressive (VAR) Models by Using the Macroeconomic Variables of Gold Prices, Borsa Istanbul (BIST) 100 Index and US Dollar-Turkish Lira (USD/TRY) Exchange Rates, Procedia Economics and Finance, vol.30, pp.3-14, 2015. ,
Forecasting performance of VAR-NN and VARMA models, Proceedings of the 2nd IMT-GT Regional Conference on Mathematics, 2006. ,
Long Short-Term Memory, Neural Comput, vol.9, issue.8, pp.1735-1780, 1997. ,
Measuring Information Transfer, Physical Review Letters, vol.85, issue.2, pp.461-464, 2000. ,
Granger causality and transfer entropy are equivalent for Gaussian variables, Physical Review Letters, vol.103, issue.23, 2009. ,
Using causal discovery for feature selection in multivariate numerical time series, Machine Learning, vol.101, issue.1-3, pp.377-395, 2014. ,
A causal feature selection algorithm for stock prediction modeling, Neurocomputing, vol.142, pp.48-59, 2014. ,
IJETT -Survey on Clustering on the Cloud by UsingMap Reduce in Large Data Applications, International Journal of Engineering Trends and Technology ,
Distributed Discord Discovery: Spark Based Anomaly Detection in Time Series, IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, pp.154-159, 2015. ,
Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms, Journal of Mathematical Modelling and Algorithms, vol.5, issue.4, pp.475-504, 2006. ,
Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00650905
Probabilistic Principal Component Analysis, Journal of the Royal Statistical Society, Series B, vol.21, 1999. ,
Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion?, Journal of Classification, vol.31, issue.3, pp.274-295, 2014. ,
Forecast: Forecasting Functions for Time Series and Linear Models, 2017. ,
Keras: Deep learning library for theano and tensorflow, 2015. ,
A new look at the statistical model identification, IEEE Transactions on Automatic Control, vol.19, issue.6, pp.716-723, 1974. ,
Significance tests harm progress in forecasting, International Journal of Forecasting, vol.23, issue.2, pp.321-327, 2007. ,
Finding Groups in Data: An Introduction to Cluster Analysis, 2009. ,
Estimating the number of clusters in a data set via the gap statistic, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.411-423, 2001. ,