On precision of stochastic optimization based on estimates from censored data

Title:

On precision of stochastic optimization based on estimates from censored data

Creator:

Volf, Petr

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:d4c60051-3936-44ad-b9e2-1745488e6e03
uuid:d4c60051-3936-44ad-b9e2-1745488e6e03

Subject:

optimization, censored data, product-limit estimate, and consistency

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In the framework of a stochastic optimization problem, it is assumed that the stochastic characteristics of optimized system are estimated from randomly right-censored data. Such a case is frequently encountered in time-to-event or lifetime studies. The analysis of precision of such a solution is based on corresponding theoretical properties of estimated stochastic characteristics. The main concern is to show consistency of optimal solution even in the random censoring case. Behavior of solutions for finite data sizes is studied with the aid of randomly generated example.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[297]-309

Source:

Kybernetika | 2014 Volume:50 | Number:3

Harvested from:

CDK

Metadata only:

false