A Strategy for Efficient Sample Selection in Simple Linear Regression Problems with Unequal per unit Sampling Costs
Simple linear regression is widely used in forestry, but often only a vaguely defined strategy for selecting sampling units is followed. Trial and error methods exist for aiding efficient sample allocation for simple linear regression purposes. These methods are computationally tedious and often impractical without the aid of a computer. This paper briefly describes a computerized iterative search procedure that can provide an efficient design for sample allocation in simple linear regression problems with equal or unequal sampling costs and balanced or unbalanced prediction intervals. Potential savings gained by employing an efficient design over other more easily derived but less efficient designs are illustrated by an example. Key words: Simple linear regression, optimal sampling design, iterative search procedure.