2nd Special Issue on Applications of Optimization Heuristics to Estimation and Modelling Problems

Computational Statistics and Data Analysis

Volumn 52, Issue 1, 2007, Pages 2-3

  Gilli, Manfred ^a   Winker, Peter ^b  

^a UNIVERSITY OF GENEVA   (Switzerland)

^b JUSTUS LIEBIG UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34548215310     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2007.04.015     Document Type: Editorial

References (15)

1. Ali, M., 2007. Synthesis of the beta-distribution as an aid to stochastic global optimization. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2006.12.011.
2. Ambrogi, F., Lama, N., Boracchi, P., Biganzoli, E., 2007. Selection of artificial neural network models for survival analysis with genetic algorithms. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.05.001.
3. Duczmal, L., 2007. A genetic algorithm for irregularly shaped spatial scan statistics. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.01.016.
4. Fitzenberger, B., Winker, P., 2007. Improving the computation of censored quantile regressions. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.01.013.
5. Hofmann, M., Gatu, C., Kontoghiorghes, E., 2007. Efficient algorithms for computing the best subset regression models for large-scale problems. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.03.017.
6. Jacobson S.H., and Yücesan E. Global optimization performance measures for generalized hill climbing algorithms. J. Global Optim. 29 (2004) 173-190
7. Jacobson S.H., Hall S.N., and McLay L.A. Visiting near-optimal solutions using local search algorithms. In: Alfredo R., and Vichi M. (Eds). COMPSTAT 2006, Proceedings in Computational Statistics (2006), Physica, Heidelberg 471-481
8. Kapetanios, G., 2007. Variable selection in regression models using non-standard optimisation of information criteria. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.04.006.
9. Keskinturk, T., Er, S., 2007. A genetic algorithm approach to determine stratum boundaries and sample sizes of each stratum in stratified sampling. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2007.03.026.
10. Krink, T., Paterlini, S., Restic, A., 2007. Using differential evolution to improve the accuracy of bank rating systems. Comput. Stat. Data Anal., this issue, doi:10.1016/j.csda.2007.02.011.
11. Staszewska, A., 2007. Representing uncertainty about response pathes: the use of heuristic optimization methods. Comput. Statist. Data Anal., this issue, doi:10.1016/j.csda.2006.12.023.
12. Winker P. Identification of multivariate AR-models by threshold accepting. Comput. Statist. Data Anal. 20 (1995) 295-307
13. Winker P., and Gilli M. Applications of optimization heuristics to estimation and modelling problems. Comput. Statist. Data Anal. 47 2 (2004) 211-223
14. Winker P., and Maringer D. The threshold accepting optimisation algorithm in economics and statistics. In: Erricos J.K., and Gatu C. (Eds). Optimisation, Econometric and Financial Analysis, Advances in Computational Management Science vol. 9 (2007), Springer, Berlin 107-125
15. Yang, Z., Tian, Z., Yuan, Z., 2007. GSA-based maximum likelihood estimation for threshold vector error correction models. Comput. Statist. Data Anal., this issue.