Kokonendji, Célestin C. and Nisa, Khoirin (2016) Generalized Variance Estimations of Normal-Poisson Models. Springer, Swiss.

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Abstract

This chapter presents three estimations of generalized variance (i.e., determinant of covariance matrix) of normal-Poisson models: maximum likelihood (ML) estimator, uniformly minimum variance unbiased (UMVU) estimator, and Bayesian estimator. First, the definition and some properties of normal-Poisson models are established. Then ML, UMVU, and Bayesian estimators for generalized variance are derived. Finally, a simulation study is carried out to assess the performance of the estimators based on their mean square error (MSE).

Item Type:	Book
Subjects:	H Social Sciences > HA Statistics Q Science > QA Mathematics
Divisions:	Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Matematika
Depositing User:	DR. KHOIRIN NISA
Date Deposited:	30 May 2017 01:35
Last Modified:	30 May 2017 01:35
URI:	http://repository.lppm.unila.ac.id/id/eprint/1946

Available Versions of this Item

• Generalized Variance Estimations of Normal-Poisson Models. (deposited 29 May 2017 06:36)
  • ANALISIS DISKRIMINAN LINIER ROBUST MENGGUNAKAN METODE VOLUME ELLIPSOID MINIMUM. (deposited 27 Mar 2018 04:45)
  • Generalized Variance Estimations of Normal-Poisson Models. (deposited 30 May 2017 01:35) [Currently Displayed]
    • Generalized Variance Estimations of Normal-Poisson Models. (deposited 27 Mar 2018 04:47)

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