Evaluates the model of the following form.
The first line of terms (through the squared terms) is included for a
two-way model, and the remaining terms are added for a three-way model.
Each unique combination of factors appears exactly once. For example,
with two factors, a two-way model is:
The coefficients are ordered as: constant, main effects, cross terms (i < j, lexicographic), squared terms, and (three-way only) triple cross terms (i < j < k), X_i**2 * X_j terms (i, then j, with i /= j), and cubed terms.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| integer(kind=int32), | intent(in) | :: | nway |
The number of interaction levels. Currently, this algorithm supports a maximum of three-way interaction. |
||
| real(kind=real64), | intent(in), | dimension(:) | :: | beta |
The model coefficients. |
|
| real(kind=real64), | intent(in), | dimension(:,:) | :: | x |
The M-by-N matrix containing the M values of each of the N factors at which to evaluate the model. |
|
| logical, | intent(in), | optional, | target, dimension(:) | :: | map |
An optional array of the same size as beta that can be used to eliminate a parameter from the model (false), or keep a parameter in the model (true). If not supplied, all parameters will be assumed to be part of the model as if the array were filled with all true values. |
The resulting M-element array.
Evaluates the model of the following form.
The first line of terms (through the squared terms) is included for a
two-way model, and the remaining terms are added for a three-way model.
Each unique combination of factors appears exactly once. For example,
with two factors, a two-way model is:
The coefficients are ordered as: constant, main effects, cross terms (i < j, lexicographic), squared terms, and (three-way only) triple cross terms (i < j < k), X_i**2 * X_j terms (i, then j, with i /= j), and cubed terms.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| class(doe_model), | intent(in) | :: | mdl |
The model to evaluate. |
||
| real(kind=real64), | intent(in), | dimension(:,:) | :: | x |
The M-by-N matrix containing the M values of each of the N factors at which to evaluate the model. |
The resulting M-element array.