TY - JOUR
T1 - Bootstrap Confidence Interval of Prediction for Small Area Estimation Based on Linear Mixed Model
AU - Novkaniza, F.
AU - Notodiputro, K. A.
AU - Sartono, B.
N1 - Publisher Copyright:
© 2018 IOP Publishing Ltd. All rights reserved.
PY - 2018/11/19
Y1 - 2018/11/19
N2 - Linear Mixed Model (LMM) analyzes the relationship between Gaussian response and predictors with either fixed and random effects. Procedures based on LMM have been used to construct estimates of the means of small areas, by exploiting auxiliary information. In this article, we show how to resample fixed effects coefficient estimates via bootstrapping and we construct nonparametric and parametric bootstrap confidence interval of predictions for small area estimation, based on mixed-effects linear models. Examples of computation for bootstrap confidence intervals of prediction are given for Battese, Harter and Fuller Data (1988).
AB - Linear Mixed Model (LMM) analyzes the relationship between Gaussian response and predictors with either fixed and random effects. Procedures based on LMM have been used to construct estimates of the means of small areas, by exploiting auxiliary information. In this article, we show how to resample fixed effects coefficient estimates via bootstrapping and we construct nonparametric and parametric bootstrap confidence interval of predictions for small area estimation, based on mixed-effects linear models. Examples of computation for bootstrap confidence intervals of prediction are given for Battese, Harter and Fuller Data (1988).
KW - mixed model
KW - nonparametric bootstrap
KW - parametric bootstrap
KW - prediction interval
UR - http://www.scopus.com/inward/record.url?scp=85068817671&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/187/1/012040
DO - 10.1088/1755-1315/187/1/012040
M3 - Conference article
AN - SCOPUS:85068817671
SN - 1755-1307
VL - 187
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012040
T2 - 4th International Seminar on Sciences, ISS 2017
Y2 - 19 October 2017 through 20 October 2017
ER -