When experiments are conducted there is always a chance of the occurrence of large measurement errors (outliers). Common identification methods like generalized least squares, maximum likelihood etc. may not converge in these situations due to the presence of oufliers. Here we present a method for t
β¦ LIBER β¦
A genetic algorithm for the maximum likelihood estimation of the parameters of sinusoids in a noisy environment
β Scribed by Ahmed S. Abutaleb
- Publisher
- Springer
- Year
- 1997
- Tongue
- English
- Weight
- 530 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0278-081X
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Modified maximum likelihood method for t
β
S. Puthenpura; N.K. Sinha
π
Article
π
1986
π
Elsevier Science
π
English
β 304 KB
Computation of the maximum likelihood es
β
M.C Spruill
π
Article
π
1986
π
Elsevier Science
π
English
β 382 KB
A hybrid genetic algorithm for the estim
β
D.Brynn Hibbert
π
Article
π
1993
π
Elsevier Science
π
English
β 923 KB
A Maximum-Likelihood Estimator of the Ge
β
JΓΌrgen Tomiuk; Volker Loeschcke
π
Article
π
1996
π
Elsevier Science
π
English
β 309 KB
Based on a recently proposed method for estimating the genetic identity between polyploid species, maximum-likelihood estimators are given for the genetic identity between polyploid species, for the ancestral degree of homozygosity and their variances. As an example, the genetic identity, the ancest
A Hybrid Genetic Algorithm for the Estim
β
G. Feng; F. Li; H. Li; H. Qu; Y. Cui
π
Article
π
2006
π
John Wiley and Sons
π
English
β 144 KB
π 2 views
Maximum likelihood estimate of the param
β
R. P. Gupta
π
Article
π
1973
π
Springer
π
English
β 93 KB