Ffacdes1: Difference between revisions
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* '''desgn''' = is a matrix of the experimental design in uncoded form | * '''desgn''' = is a matrix of the experimental design in uncoded form | ||
* '''col_ID''' = is a cell array of strings describing the multiplicative origin of each column; one col for each coefficient to potentially be calculated where: | * '''col_ID''' = is a cell array of strings describing the multiplicative origin of each column; one col for each coefficient to potentially be calculated where: | ||
* the first k cells describe the original main factors | ** the first k cells describe the original main factors | ||
* the remaining cells describe the various interactions among main factors. | ** the remaining cells describe the various interactions among main factors. | ||
* '''alias_ID''' = is a cell array of logicals describing the alias structure of the selected design; one row per coefficient/X-column. Multiplying a given logical by the full set of characters representing the factors yields the alias relationship for that row/coefficient. | * '''alias_ID''' = is a cell array of logicals describing the alias structure of the selected design; one row per coefficient/X-column. Multiplying a given logical by the full set of characters representing the factors yields the alias relationship for that row/coefficient. | ||
:: <pre>ABCDEF .* [1 0 0 1 1 0] = ADE</pre> | :: <pre>ABCDEF .* [1 0 0 1 1 0] = ADE</pre> | ||
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===See Also=== | ===See Also=== | ||
[[boxbehnken]], [[ccdface]], [[ccdsphere]], [[doegen]], [[doescale]], [[factdes]] | |||
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Latest revision as of 16:08, 30 May 2013
Purpose
Output a fractional factorial design matrix.
Synopsis
- desgn = ffacdes1(k,p)
- [desgn, col_ID, alias_ID, res] = ffacdes1(k,p,options)
Description
FFACDES1 outputs a 2(k-p) fractional factorial design of experiments. The design is constructed such that the highest order interaction term is confounded. This is one way to select a fractional factorial. Input k is the total number of factors in the design and p is the number of confounded factors {default: p = 1}. Note that it is required that p < k. Output desgn is the experimental design matrix.
Inputs
- k = total number of factors in the design.
Optional Inputs
- p = numerical indicator of the fraction desired (default = 1)
- 1 : Half Fraction
- 2 : Quarter Fraction
- 3 : Eighth Fraction
- 4 : Sixteenth Fraction
- Note: Only fractionation up to 1/16 presently supported
Outputs
- desgn = experimental design matrix
If the dso option is false, the outputs include:
- desgn = is a matrix of the experimental design in uncoded form
- col_ID = is a cell array of strings describing the multiplicative origin of each column; one col for each coefficient to potentially be calculated where:
- the first k cells describe the original main factors
- the remaining cells describe the various interactions among main factors.
- alias_ID = is a cell array of logicals describing the alias structure of the selected design; one row per coefficient/X-column. Multiplying a given logical by the full set of characters representing the factors yields the alias relationship for that row/coefficient.
ABCDEF .* [1 0 0 1 1 0] = ADE
- res = resolution of the selected design.