Factdes: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Full factorial design of experiments. | |||
===Synopsis=== | ===Synopsis=== | ||
:desgn = factdes( | : desgn = factdes(k,levl) | ||
: desgn = factdes(levls) | |||
===Description=== | ===Description=== | ||
Create a full factorial design of experiments. | |||
====Inputs==== | ====Inputs==== | ||
* ''' | * '''k''' = the number of factors in the design i.e. the number of columns in the output (desgn), and (levl) is the number of levels (default = 2). All factors are created at the given number of levels. To create a DOE with a different number of levels in each factor, use form (B) of the inputs. | ||
====Optional Inputs==== | ====Optional Inputs==== | ||
* ''' | * '''levls''' = can be provided as a single input containing a vector equal in length to the number of factors desired and indicating the number of levels for each of those factors. For example: [2 2 3] would generate a 3-factor model with two factors at 2 levels and one at 3 levels. | ||
====Outputs==== | ====Outputs==== | ||
* '''desgn''' = experimental design | * '''desgn''' = Output (desgn) is the matrix of the experimental design. If levl=2 then this gives a 2^k design. | ||
===See Also=== | ===See Also=== | ||
[[distslct]], [[doptimal]], [[ffacdes1]], [[stdsslct]] | [[distslct]], [[doptimal]], [[ffacdes1]], [[stdsslct]] | ||
Revision as of 11:49, 1 September 2011
Purpose
Full factorial design of experiments.
Synopsis
- desgn = factdes(k,levl)
- desgn = factdes(levls)
Description
Create a full factorial design of experiments.
Inputs
- k = the number of factors in the design i.e. the number of columns in the output (desgn), and (levl) is the number of levels (default = 2). All factors are created at the given number of levels. To create a DOE with a different number of levels in each factor, use form (B) of the inputs.
Optional Inputs
- levls = can be provided as a single input containing a vector equal in length to the number of factors desired and indicating the number of levels for each of those factors. For example: [2 2 3] would generate a 3-factor model with two factors at 2 levels and one at 3 levels.
Outputs
- desgn = Output (desgn) is the matrix of the experimental design. If levl=2 then this gives a 2^k design.