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2013, 1st ed., Numerical mathematics and scientific computation, ISBN 9780199655410, Volume 9780199655410, xv, 391
Book
Journal Article
Archives of Computational Methods in Engineering, ISSN 1134-3060, 3/2012, Volume 19, Issue 1, pp. 51 - 124
Journal Article
Journal Article
2016, 1, Chapman & Hall/CRC Monographs on Statistics & Applied Probability, ISBN 9781482219593, Volume 149, 298
State-space models are a very flexible class of models used primarily in time series analysis. This book provides a synthesis of recent research in this area,... 
Economics | State-space methods | Statistics for Business | Mathematics & Statistics for Engineers | Statistical Theory & Methods | Finance & Economics | Time-series analysis
eBook
Journal of Econometrics, ISSN 0304-4076, 04/2019, Volume 209, Issue 2, pp. 391 - 406
Random subspace methods are a new approach to obtain accurate forecasts in high-dimensional regression settings. Forecasts are constructed by averaging over... 
Random subspace | Dimension reduction | Forecasting | ECONOMIC TIME-SERIES | REGRESSION | DATABASE | Top | RANDOM PROJECTION | SHRINKAGE | JOHNSON-LINDENSTRAUSS | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS | RANDOM PROJECTIONS | Forecasts | Weighting | Normal distribution | Random variables | Regression analysis | Macroeconomics
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Parallel Computing, ISSN 0167-8191, 04/2012, Volume 38, Issue 4-5, pp. 245 - 259
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Journal Article