Fractional factorial split-plot designs are widely used when it is impractical to perform fractional experiments in a completely random order. When there too many subplots per whole plot, or few plots, with replicated settings of the plot factors preferred. However, such an important study undeveloped literature. This paper considers WP from viewpoint clear effects. We investigate sufficient an...

In some experiments, the levels of factors are difficult to change; then fractional factorial split-plot (FFSP) designs suitable for selection. an FFSP design, divided into two classes—the whole plot (WP) and subplot (SP) factors. selection WP can affect that SP factors, which attracts much attention Paying more a new optimality criterion selecting such is proposed. The robustness proposed meth...

We introduce a new method for generating optimal split-plot designs. These designs are optimal in the sense that they are efficient for estimating the fixed effects of the statistical model that is appropriate given the split-plot design structure. One advantage of the method is that it does not require the prior specification of a candidate set. This makes the production of split-plot designs ...

We have investigated the processes of community assembly using size classes of trees. Specifically our work examined (1) whether point process models incorporating an effect of size-class produce more realistic summary outcomes than do models without this effect; (2) which of three selected models incorporating, respectively environmental effects, dispersal and the joint-effect of both of these...