This paper proposes an elegant, yet straightforward, model for classifying linear mixtures. A linear mixture is defined as a random vector y in which the variable are a (nonnegative) weighted average of corresponding variables, assumed to characterize g component groups. These weights are referred t
Using mixtures of Weibull distributions to estimate mixing proportions
โ Scribed by Wayne A. Woodward; Richard F. Gunst
- Publisher
- Elsevier Science
- Year
- 1987
- Tongue
- English
- Weight
- 872 KB
- Volume
- 5
- Category
- Article
- ISSN
- 0167-9473
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Fisher's method of maximum likelihood breaks down when applied to the problem of estimating the five parameters of a mixture of two normal densities from a continuous random sample of size n. Alternative methods based on minimumdistance estimation by grouping the underlying variable are proposed. Si
procedure is presented for finding maximum likelihood estimates of the parameters of a mixture of two Weibull distributions. Estimation of a nonlinear discriminant function on the basis of small sample size is considered. Throughout simulation experiments, the total probabilities of misclassificatio