Version 6.18 of the Gendex DOE Toolkit has 12 modules (and the bonus module Sudoku). The function of each module is described below. You can get access to the documentation of each module by clicking on the corresponding module in the left panel.
ALPHAα-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.
IBDAn 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 (1981 Biometrika) in terms of the efficiency factor of the designs.
CIBDCyclic IBDs are IBDs generated by the cyclic development of one or more suitably chosen initial blocks. Cyclic IBDs account 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.
RCDA 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.
RRCDA 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.
FEADOFEADO 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.
MIGAMIGA constructs minimum G-aberration designs. The minimum G-aberration criterion proposed by Tang & Deng (1999) is a generalized version of the popular minimum aberration criterion of Fries & Hunter (1980). Designs constructed by MIGA include both regular and non-regular 2-level fractional factorial designs.
SODSOD constructs second order response surface designs. The constructed designs include Box-Behnken designs, Draper-Lin small designs, etc. SORD can also augment hard-to-change (HTC) factors with additional easy-to-change (ETC) factors. Split-plot RSDs which satisfy the balanced equivalent estimation property expressed in equation (4) of Parker, et al. (2006) can be constructed by this facility.
CUTCUT uses the extension of the algorithm in Nguyen (2001 Austral. &New Zealand J. of Statist.) for multi-dimensional blocking fractional factorial designs (FFDs) and response surface designs (RSDs). The CUT approach to blocking a design is to find a suitable unblocked design (constructed by other Gendex modules such as FEADO, MIGA and SORD) and allocate the n runs of this design to blocks, or rows and columns, etc.
RATRAT 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).
NOANOA 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.
LHDLatin hypercubes (LHs) were designs introduced by McKay, Beckman & Conover (1979) for computer experiments. An nxk LH can be represented by a design matrix Xnxk with n rows (runs) and k columns (factors), each of which includes n uniformly spaced levels. An LH is called an orthogonal LH (OLH) if each pair of columns of this LH has zero correlation. LHD is a Gendex module for constructing near-OLHs with good space-filling property.
SUDOKUSudoku is a logic-based number-placement puzzle. The objective is to fill a 9x9 grid so that each column, each row, and each of the nine 3x3 boxes (also called blocks or regions) contains the digits from 1 to 9 only one time each. The puzzle provides a partially completed grid. SUDOKU is a Sudoku puzzle solver and generator.
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