Why the Monte Carlo method is so important today.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 386, doi. 10.1002/wics.1314
- By:
- Publication type:
- Article
Works matching IS 19395108 AND DT 2014 AND VI 6 AND IP 6
Results: 8
1
2
Hierarchical modeling in spatial epidemiology.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 405, doi. 10.1002/wics.1315
- By:
- Publication type:
- Article
3
Community detection in large-scale networks: a survey and empirical evaluation.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 426, doi. 10.1002/wics.1319
- By:
- Publication type:
- Article
4
Volatility analysis in high-frequency financial data.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 393, doi. 10.1002/wics.1330
- By:
- Publication type:
- Article
5
Simulation-based estimation: a case study in oncology ( SIMEST) and a case study in portfolio selection ( SIMUGRAM).
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 379, doi. 10.1002/wics.1320
- By:
- Publication type:
- Article
6
Analyzing complex mathematical model behavior by partial least squares regression-based multivariate metamodeling.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 440, doi. 10.1002/wics.1325
- By:
- Publication type:
- Article
7
Semiparametric hidden Markov models: identifiability and estimation.
- Published in:
- WIREs: Computational Statistics, 2014, v. 6, n. 6, p. 418, doi. 10.1002/wics.1326
- By:
- Publication type:
- Article
8
Issue information.
- Published in:
- 2014
- Publication type:
- Other