Statistical Inference on the General Linear Models under Heteroscedasticity
نویسندگان
چکیده
Assuming a general linear model with unknown and possibly unequal normal error variances, the interest is to develop a one-sample procedure to handle the statistical problems involving point estimation, confidence region, and general linear hypotheses on regression parameters. The sampling procedure is to split up each single sample of size ni at a controllable regressor’s data point into two portions, the first consisting of the first ni − 1 observations for initial estimation and the second consisting of the remaining one for overall use in the final estimation in order to define a weighted sample mean on all sample observations at each data point. Then, the weighted sample mean is used to serve as a basis for parameter estimates and test
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