Estimation of the Minimum of a Function Using Order Statistics
β Scribed by Laurens de Haan
- Book ID
- 125237049
- Publisher
- American Statistical Association
- Year
- 1981
- Tongue
- English
- Weight
- 525 KB
- Volume
- 76
- Category
- Article
- ISSN
- 0162-1459
- DOI
- 10.2307/2287851
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π SIMILAR VOLUMES
In this paper, we consider the problem of approximating the location, x 0 # C, of a maximum of a regresion function, %(x), under certain weak assumptions on %. Here C is a bounded interval in R. A specific algorithm considered in this paper is as follows. Taking a random sample X 1 , ..., X n from
Let Yi -N(Bi, o?), i = 1, . . . , p, be independently distributed, where Bi and of are unknown. A Bayesian approach is used to estimate the first two moments of the minimum order statistic, W = min( Y I , . . . , Y,). In order to compute the Bayes estimates, one has to evaluate the predictive densit