For a perfectly balanced experimental design ( such as a factorial design or balanced partial factorial design ), the leverage for each point is p / n, the number of parameters divided by the number of points.
42.
For a perfectly balanced experimental design ( such as a factorial design or balanced partial factorial design ), the leverage for each point is p / n, the number of parameters divided by the number of points.
43.
In practice, one rarely encounters " l " > 2 levels in fractional factorial designs, since response surface methodology is a much more experimentally efficient way to determine the relationship between the experimental response and factors at multiple levels.
44.
If the number of combinations in a full factorial design is too high to be logistically feasible, a fractional factorial design may be done, in which some of the possible combinations ( usually at least half ) are omitted.
45.
If the number of combinations in a full factorial design is too high to be logistically feasible, a fractional factorial design may be done, in which some of the possible combinations ( usually at least half ) are omitted.
46.
Robust parameter designs very similar to fractional factorial designs ( FFDs ) in that the optimal design can be found using Hadamard matrices, principles of effect hierarchy and factor sparsity are maintained, and aliasing is present when full RPDs are fractionated.
47.
A factorial design allows the effect of several factors and even interactions between them to be determined with the same number of trials as are necessary to determine any one of the effects by itself with the same degree of accuracy.
48.
Consequently, fractional factorial design is commonly used to reduce the number of profiles that have to be evaluated, while ensuring enough data are available for statistical analysis, resulting in a carefully controlled set of " profiles " for the respondent to consider.
49.
The subset is chosen so as to exploit the sparsity-of-effects principle to expose information about the most important features of the problem studied, while using a fraction of the effort of a full factorial design in terms of experimental runs and resources.
50.
Then each of the three large plots is subdivided into subplots of which 3 are control plots, and 21 or 18 receive different quantities and combinations of fertilizer nitrogen, phosphorus and potassium, in a fractional factorial design as suggested by Ramamoorthy and Velayutham in 1971.
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