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A graph approach to generate all possible regression submodels

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  • Gatu, Cristian
  • Yanev, Petko I.
  • Kontoghiorghes, Erricos J.

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  • Gatu, Cristian & Yanev, Petko I. & Kontoghiorghes, Erricos J., 2007. "A graph approach to generate all possible regression submodels," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 799-815, October.
    • Handle: RePEc:eee:csdana:v:52:y:2007:i:2:p:799-815
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    References listed on IDEAS

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    1. Kontoghiorghes, E. J. & Clarke, M. R. B., 1995. "An alternative approach for the numerical solution of seemingly unrelated regression equations models," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 369-377, April.
    2. Martin S. Ridout, 1988. "An Improved Branch and Bound Algorithm for Feature Subset Selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(1), pages 139-147, March.
    3. Cristian Gatu & Erricos Kontoghiorghes, 2005. "Efficient strategies for deriving the subset VAR models," Computational Management Science, Springer, vol. 4(4), pages 253-278, November.
    4. Cristian Gatu & Erricos Kontoghiorghes, 2002. "A branch and bound algorithm for computing the best subset regression models," Computing in Economics and Finance 2002 294, Society for Computational Economics.
    5. M. R. B. Clarke, 1981. "A Givens Algorithm for Moving from One Linear Model to Another Without Going Back to the Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 30(2), pages 198-203, June.
    6. E. L. Lawler & D. E. Wood, 1966. "Branch-and-Bound Methods: A Survey," Operations Research, INFORMS, vol. 14(4), pages 699-719, August.
    7. Hofmann, Marc & Gatu, Cristian & Kontoghiorghes, Erricos John, 2007. "Efficient algorithms for computing the best subset regression models for large-scale problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 16-29, September.
    8. Gatu, Cristian & Kontoghiorghes, Erricos J. & Gilli, Manfred & Winker, Peter, 2008. "An efficient branch-and-bound strategy for subset vector autoregressive model selection," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1949-1963, June.
    9. Gatu, Cristian & Kontoghiorghes, Erricos J., 2006. "Estimating all possible SUR models with permuted exogenous data matrices derived from a VAR process," Journal of Economic Dynamics and Control, Elsevier, vol. 30(5), pages 721-739, May.
    10. Smith, D. M. & Bremner, J. M., 1989. "All possible subset regressions using the QR decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 7(3), pages 217-235, February.
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    1. Hofmann, Marc & Gatu, Cristian & Kontoghiorghes, Erricos John, 2007. "Efficient algorithms for computing the best subset regression models for large-scale problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 16-29, September.
    2. Fossati, Sebastian, 2012. "Covariate unit root tests with good size and power," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3070-3079.
    3. Smirnov, Oleg A. & Anselin, Luc E., 2009. "An O(N) parallel method of computing the Log-Jacobian of the variable transformation for models with spatial interaction on a lattice," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2980-2988, June.
    4. Postiglione, Paolo & Benedetti, Roberto & Lafratta, Giovanni, 2010. "A regression tree algorithm for the identification of convergence clubs," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2776-2785, November.
    5. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    6. McNicholas, P.D. & Murphy, T.B. & McDaid, A.F. & Frost, D., 2010. "Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 711-723, March.
    7. Luca Insolia & Ana Kenney & Francesca Chiaromonte & Giovanni Felici, 2022. "Simultaneous feature selection and outlier detection with optimality guarantees," Biometrics, The International Biometric Society, vol. 78(4), pages 1592-1603, December.
    8. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    9. Yang, Guijun & Wang, Zhigang & Deng, Wei, 2010. "Unbiased generalized quasi-regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 779-789, March.
    10. Paroli, Roberta & Spezia, Luigi, 2008. "Bayesian inference in non-homogeneous Markov mixtures of periodic autoregressions with state-dependent exogenous variables," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2311-2330, January.
    11. Siniksaran, Enis, 2008. "A geometric interpretation of Mallows' Cp statistic and an alternative plot in variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3459-3467, March.
    12. Gatu, Cristian & Kontoghiorghes, Erricos J. & Gilli, Manfred & Winker, Peter, 2008. "An efficient branch-and-bound strategy for subset vector autoregressive model selection," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1949-1963, June.

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