1 ALPHA
α-design is a new class of resolvable incomplete block design (IBD) introduced by Patterson & Williams (1976 Biometrika). Since their introduction, α-designs have become popular among designers of experiments as nowadays, the flexibility of the design has succeeded computational simplicity as their criterion in design selection. ALPHA uses the extension of the algorithm in Nguyen (2002 Advances in Statistics, Combinatorics and Related Areas) to produce α-designs with up to 10,000 treatments. Click here to get access to the documentation of this module.2 IBD
An IBD of size (v,k,r) is an arrangement of v treatments set out in blocks of size k (<v) such that each treatment is replicated r times. IBD uses the algorithm in Nguyen (1993 Commun. Statist., 1994 Technometrics) to produce optimal or near-optimal IBDs. These IBDs can be non-resolvable or t-resolvable and are comparable with α-designs and generalized cyclic designs of Hall & Jarrett (1981Biometrika) in terms of the efficiency factor of the designs. Click here to get access to the documentation of this module.3 CIBD
Cyclic IBDs are IBDs generated by the cyclic development of one or more suitably chosen initial blocks. Cyclic IBDs accounts for a large number of balanced IBDs in Statistical tables for biological, agricultural and medical research of Fisher & Yates (1963) and Rao (1961 Sankhya). They also provide many efficient partially balanced IBDs, catalogued in Tables of two-associates-class partially balanced designs of Clatworthy (1973). CIBD uses the extension of the algorithm in Nguyen (2002 Advances in Statistics, Combinatorics and Related Areas) to produce cyclic IBDs with up to 10,000 treatments. Click here to get access to the documentation of this module.4 RCD
A row-column design (RCD) of size (v,k,b) is an arrangement of v treatments set out in kxb array such that each treatment is replicated r times (vr=kb). RCD uses Nguyen (1997 Computing Science & Statist.) to construct optimal row-column designs by permuting the treatments within the blocks of a block design used as the column component of an RCD. Click here to get access to the documentation of this module.RRCD
A resolvable row-column design of size (r,k,s) is an arrangement of r kxs arrays each of which is a complete replicate of v=ks treatments. RRCD uses Nguyen & Williams (1993 Austral. J. Statist.) to construct optimal resolvable row-column designs by permuting the treatments within the blocks of a resolvable block design used as the column component of a resolvable RCD. Click here to get access to the documentation of this module.6 FEADO
FEADO uses the fast Fedorov's exchange algorithm described in Nguyen & Miller (1992 Computational Statist. & Data Analysis), Miller & Nguyen (1994 Applied Statistics) and Nguyen & Piepel (2005 Quality Technology & Quantitative Management) to construct D- and G-optimal 2-level, 3-level and mixed level fractional factorial designs and response surface designs and designs for irregular-shaped regions such as mixture designs. FEADO can also augment an existing design with additional runs. Click here to get access to the documentation of this module.7 FRAC
FRAC uses the extension of the algorithm in Nguyen (1996a Technometrics) to construct orthogonal and near-orthogonal 2-level and mixed level fractional factorial designs of resolution III, IV and V and response surface designs. FRAC can also augment an existing design with additional 2-level factors. Click here to get access to the documentation of this module.8 CUT
CUT uses the extension of the algorithm in Nguyen (2001 Austral. & New Zealand J. of Statist.) to block the fractional factorial designs and response surface designs which are produced by other Gendex modules such as FEADO and FRAC. The current version of this module can also construct balanced equivalent estimation 2nd-order split-plot designs. Click here to get access to the documentation of this module.9 RAT
RAT uses an unpublished algorithm of Nguyen (1998) to construct trend-free fractional factorial designs and response surface designs (designs which are robust against time trends). Click here to get access to the documentation of this module.10 NOA
NOA uses the the algorithms in Nguyen (1996a Technometrics,1996b Technometrics) and Nguyen & Liu (2008 Computational Statistics & Data Analysis) to construct mixed-level orthogonal arrays, near-orthogonal arrays and supersaturated designs). NOA can augment existing arrays with additional columns. Click here to get access to the documentation of this module.©2008 Design Computing