Lihat Juga

• There have been two main topics developed by statisticians in a survey, i.e. sampling techniques and estimation methods. The current issues in estimation methods related to estimation of a particular domain having small size of samples or, in more extreme cases, there is no sample available for direct estimation. Sample survey data provide effective reliable estimators of totals and means for large area and domains. But it is recognized that the usual direct survey estimator performing statistics for a small area, have unacceptably large standard errors, due to the circumstance of small sample size in the area. The most commonly used models for this case, usually in small area estimation, are based on generalized linear mixed models. Some time happened that some surveys are carried out periodically so that the estimation could be improved by incorporating both the area and time random effects. In this paper we propose a state space model which accounts for the two random effects and is based on two equation, namely transition equation and measurement equation. Based on a evaluation criterion, the proposed hierarchical Bayes estimator turns out to be superior to both estimated best linear unbiased prediction (BLUP) and the direct survey estimator. The posterior variances which measure accuracy of the hierarchical Bayes estimates are always smaller than the corresponding variances of the BLUP and the direct survey estimates
  oleh: Sadik, Kusman; FMIPA IPB
  Terbitan: (2012)
• A SIMULATION STUDY OF LOGARITHMIC TRANSFORMATION MODEL IN SPATIAL E MPIRICAL BEST LINEAR UNBIASED PREDICTION (SEBLUP) METHOD OF SMALL AREA ESTIMATION
  oleh: Zainuddin, Hazan Azhari; Bogor Agricultural University (IPB), et al.
  Terbitan: (2015)
• PENDEKATAN GENERAL LINEAR MIXED MODEL PADA SMALL AREA ESTIMATION
  oleh: Notodiputro, Khairil A.; Departemen Statistika FMIPA-IPB, et al.
  Terbitan: (2005)
• Small Area Estimation with Measurement Error in t Distributed Covariate Variable
  oleh: Hariyanto, Soni; Department of Statistics, Faculty of Mathematics and Natural Science, IPB University, Bogor 16680, Indonesia, et al.
  Terbitan: (2020)
• KAJIAN SIMULASI KETAKNORMALAN PENGARUH ACAK DAN BANYAKNYA DERET DATA LONGITUDINAL DALAM PEMODELAN BERSAMA (JOINT MODELING) (Simulation Study of Random Effects Nonnormality and Number of Longitudinal Data Series in Joint Modeling)
  oleh: ., Indahwati; Departemen Statistika FMIPA – IPB, et al.
  Terbitan: (2011)