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Row exchange
dRE = rowexch(nfactors,nruns)
[dRE,X] = rowexch(nfactors,nruns)
[dRE,X] = rowexch(nfactors,nruns,model)
[dRE,X] = rowexch(...,param1,val1,param2,val2,...)
dRE = rowexch(nfactors,nruns) uses a rowexchange algorithm to generate a Doptimal design dRE with nruns runs (the rows of dRE) for a linear additive model with nfactors factors (the columns of dRE). The model includes a constant term.
[dRE,X] = rowexch(nfactors,nruns) also returns the associated design matrix X, whose columns are the model terms evaluated at each treatment (row) of dRE.
[dRE,X] = rowexch(nfactors,nruns,model) uses the linear regression model specified in model. model is one of the following strings:
'linear' — Constant and linear terms. This is the default.
'interaction' — Constant, linear, and interaction terms
'quadratic' — Constant, linear, interaction, and squared terms
'purequadratic' — Constant, linear, and squared terms
The order of the columns of X for a full quadratic model with n terms is:
The constant term
The linear terms in order 1, 2, ..., n
The interaction terms in order (1, 2), (1, 3), ..., (1, n), (2, 3), ..., (n–1, n)
The squared terms in order 1, 2, ..., n
Other models use a subset of these terms, in the same order.
Alternatively, model can be a matrix specifying polynomial terms of arbitrary order. In this case, model should have one column for each factor and one row for each term in the model. The entries in any row of model are powers for the factors in the columns. For example, if a model has factors X1, X2, and X3, then a row [0 1 2] in model specifies the term (X1.^0).*(X2.^1).*(X3.^2). A row of all zeros in model specifies a constant term, which can be omitted.
[dRE,X] = rowexch(...,param1,val1,param2,val2,...) specifies additional parameter/value pairs for the design. Valid parameters and their values are listed in the following table.
Parameter  Value 

'bounds'  Lower and upper bounds for each factor, specified as a 2bynfactors matrix. Alternatively, this value can be a cell array containing nfactors elements, each element specifying the vector of allowable values for the corresponding factor. 
'categorical'  Indices of categorical predictors. 
'display'  Either 'on' or 'off' to control display of the iteration counter. The default is 'on'. 
'excludefun'  Handle to a function that excludes undesirable runs. If the function is f, it must support the syntax b = f(S), where S is a matrix of treatments with nfactors columns and b is a vector of Boolean values with the same number of rows as S. b(i) is true if the ith row S should be excluded. 
'init'  Initial design as an nrunsbynfactors matrix. The default is a randomly selected set of points. 
'levels'  Vector of number of levels for each factor. 
'maxiter'  Maximum number of iterations. The default is 10. 
options  A structure that specifies whether to run in parallel, and specifies the random stream or streams. Create the options structure with statset. Option fields:

'tries'  Number of times to try to generate a design from a new starting point. The algorithm uses random points for each try, except possibly the first. The default is 1. 
Suppose you want a design to estimate the parameters in the following threefactor, seventerm interaction model:
Use rowexch to generate a Doptimal design with seven runs:
nfactors = 3; nruns = 7; [dRE,X] = rowexch(nfactors,nruns,'interaction','tries',10) dRE = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 X = 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Columns of the design matrix X are the model terms evaluated at each row of the design dRE. The terms appear in order from left to right: constant term, linear terms (1, 2, 3), interaction terms (12, 13, 23). Use X to fit the model, as described in Linear Regression, to response data measured at the design points in dRE.