Empirical Best Predictor Under Area-Level Gamma Mixed Model

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F18%3A00325051" target="_blank" >RIV/68407700:21340/18:00325051 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Empirical Best Predictor Under Area-Level Gamma Mixed Model
Original language description
In practise we can encounter many problems where it is useful to employ small area estimation (SAE) methods to obtain reliable estimates of characteristics of interest (e.g. means, totals). This contribution deals with an empirical best predictor (EBP) under an arealevel gamma mixed model where responses have the gamma distribution. To obtain estimates of regression parameters and predictors of random effects, the ML Laplace approximation algorithm is used. Subsequently, an algorithm for calculating the EBP is derived. Simulation experiments are conducted to check the behaviour of the EBP and the plug-in estimator.
Czech name
—
Czech description
—

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
SPMS 2018 - Stochastic and Physical Monitoring Systems, Proceedings of the international conference
ISBN
978-80-01-06501-3
ISSN
—
e-ISSN
—
Number of pages
9
Pages from-to
1-9
Publisher name
Česká technika - nakladatelství ČVUT
Place of publication
Praha
Event location
Dobřichovice
Event date
Jun 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)