The Bayes choice of an experiment in estimating a success probability

Alicja Jokiel-Rokita, and Ryszard Magiera. "The Bayes choice of an experiment in estimating a success probability." Applicationes Mathematicae 29.2 (2002): 135-144. <http://eudml.org/doc/278886>.

@article{AlicjaJokiel2002,
abstract = {A Bayesian method of estimation of a success probability p is considered in the case when two experiments are available: individual Bernoulli (p) trials-the p-experiment-or products of r individual Bernoulli (p) trials-the $p^\{r\}$-experiment. This problem has its roots in reliability, where one can test either single components or a system of r identical components. One of the problems considered is to find the degree r̃ of the $p^\{r̃\}$-experiment and the size m̃ of the p-experiment such that the Bayes estimator based on m̃ observations of the p-experiment and N-m̃ observations of the $p^\{r̃\}$-experiment minimizes the Bayes risk among all the Bayes estimators based on m observations of the p-experiment and N-m observations of the $p^\{r\}$-experiment. Another problem is to sequentially select some combination of these two experiments, i.e., to decide, using the additional information resulting from the observation at each stage, which experiment should be carried out at the next stage to achieve a lower posterior expected loss.},
author = {Alicja Jokiel-Rokita, Ryszard Magiera},
journal = {Applicationes Mathematicae},
keywords = {allocation; Bayes estimation; Bayes risk; loss function; posterior expected loss; prior distribution},
language = {eng},
number = {2},
pages = {135-144},
title = {The Bayes choice of an experiment in estimating a success probability},
url = {http://eudml.org/doc/278886},
volume = {29},
year = {2002},
}

TY - JOUR
AU - Alicja Jokiel-Rokita
AU - Ryszard Magiera
TI - The Bayes choice of an experiment in estimating a success probability
JO - Applicationes Mathematicae
PY - 2002
VL - 29
IS - 2
SP - 135
EP - 144
AB - A Bayesian method of estimation of a success probability p is considered in the case when two experiments are available: individual Bernoulli (p) trials-the p-experiment-or products of r individual Bernoulli (p) trials-the $p^{r}$-experiment. This problem has its roots in reliability, where one can test either single components or a system of r identical components. One of the problems considered is to find the degree r̃ of the $p^{r̃}$-experiment and the size m̃ of the p-experiment such that the Bayes estimator based on m̃ observations of the p-experiment and N-m̃ observations of the $p^{r̃}$-experiment minimizes the Bayes risk among all the Bayes estimators based on m observations of the p-experiment and N-m observations of the $p^{r}$-experiment. Another problem is to sequentially select some combination of these two experiments, i.e., to decide, using the additional information resulting from the observation at each stage, which experiment should be carried out at the next stage to achieve a lower posterior expected loss.
LA - eng
KW - allocation; Bayes estimation; Bayes risk; loss function; posterior expected loss; prior distribution
UR - http://eudml.org/doc/278886
ER -