On Bayesian Estimation of Random Two-way Classification Model with Interaction

This research deals with the estimation of linear random two-way classification model with interaction, containing four parameters. These are: variance of effect A, variance of effect variance of interaction AB and variance of random error. These parameters are estimated through using Bayes Quadratic Unbiased Estimator (BAQUE).The prior information obtained by using variance analysis technique to represent prior estimates of these parameters. Then, the prior distribution is considered as a uniform distribution. BAQUE approach is applied to real data obtained from Mosul University/ College of Agriculture and Forestry / Department of Crops, and these data represent the development of planting yellow corn that the development has three factors which are the corn type, the quantity of nitrogen fertilizer and the interaction between them. Then a random sample was taken from these data to get the random model. The results of estimates that have been obtained are very encouraging.