Volume 3 • Issue 1 • PP: 34-41 • 2024
On The Bayesian Estimation of Parameters of SQDM
View PDF Abstract
This work is concerned with the problem of estimating parameters of spatial quadratic models by Bayesian technique (SQDM). This technique involves the prior information of the first and second moment of the parameters, where its estimation model is called the Bayesian quadratic unbiased estimator. The results of the estimation are taken in compared with the estimates of minimum norm quadratic unbiased estimators.
Keywords
References
[1] Jaber, Adnan shamkhi, Dhawiya Salman Hassan (1988), introduction to Operations Research, Ministry of higher education and scientific research, University of Baghdad.
[2] Abdul Rahman, Nibal Sabah (2001) linear spatial heterogeneity model with unpublished master thesis application, Mosul University, Mosul, Iraq.
[3] Yunus (1996) Bayes estimation of the spatial covariance function with two parameters and three parameters unpublished Master Thesis, University of Mosul, Mosul, Iraq.
[4] Cressie, N. (1993): Statistics for Spatial Data. John Wiley, NewYork.
[5] Delfiner, P. (1976): Linear Estimation of Nonstationary spatial phenomena. In: Guarascio, M., David and Huijbregts, C. (Ed.). advances Geostatistics in the Mining Industry Reidel, D. publishing Co. Holland, pp. 49.68.
[6] Davies, W.S. (2002) : Quantitative Methods, Bayesian Inference. Progressin Human Geography, Vol. 26, 4, P. 553.
[7] Diggle, P. J. (2002): Bayesian Inference in Gaussian Model Geostatistics. Geographical and Enviro Mental Modeling, Vol. 6, 2, P. 129.
[8] Hogg, R. V. and Craig A. T. (1978): Introduction to mathematical statistics. Macmillan publishing Co., Inc. New York.
[9] Kleffe, J. and Pincus, R. (1974): Bayes and Best Quadratic unbiased Estimators for Parameters of the covariance Matrix in a Normal Linear Model. Math. Operations forsch. U. Statist., 5, Heft 1, S. 43-67.
[10] Krige, D. G. (1976): Some Basic Consideration in the Application of Geostatistics to the valuation of ore in south African Gold Mines, Journal of the South African Institute of Mining and Metallurgy. 383-391.
[11] Marshall, R. J. and Mardia, K. V. (1985): Minimum Norm Quadratic Estimation of components of spatial covariance. Math. Geol., Vol. 17, No.5, pp.517-525.
[12] Rao, C. R. and Kleffe, J. (1988): Estimation of Variance Components and Application. Worth-Holland, New York.
Cite This Article
Choose your preferred format