|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 2 van 7 gevonden artikelen
| Titel: |
Bayesian subset selection for additive and linear loss function |
| Auteur: |
Mieseke, Klaus-J. |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 8 (1979) nr. 12 pagina's 1205-1226 |
| Jaar: |
1979 |
| Inhoud: |
Given k independent samples [image omitted] of common size n from k populations πj,…,πk with distribution [image omitted] the problem is to select a non-empty subset [image omitted] form {πj,…,πk}, which is associated with "good" (large) θ-values. We consider this problem from a Bayesian approach. By choosing additive [image omitted] and especially linear [image omitted] loss functions we try to fill a gap lying in between the results of Deely and Gupta (1968) and more recent papers due to Goel and Rubin (1977), Gupta and Hsu (1978) and other authors. It is shown that under acertain "normal model" Seal's procedure turns out to be Bayes w.r.t. an unrealistic loss function where as Gupta's maximunl means procedure turns out to be ( for large n) asymptotically Bayes w.r. t. more realistic additive loss functions. Finally, in the appendix sonie bounds for [image omitted] are derived (where [image omitted] are fixed known and [image omitted] to approximate the Bayes rules w.r.t. linear loss functions in cases where n is finite. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 2 van 7 gevonden artikelen
| << vorige | volgende >> |