The steepAscent.c
class represents a steepest ascent algorithm in a factorial design context. This class is used for optimizing designs based on iterative improvements.
name
A character string representing the name of the steep ascent design.
X
A data frame containing the design matrix for the steepest ascent procedure. This matrix represents the factors and their levels at each iteration.
response
A data frame containing the response values associated with the design matrix.
.response()
Get and set the `response` values in an object of class `steepAscent.c`.
steepAscent.c$.response(value)
value
A data frame or numeric vector to set as the new `response`. If missing, returns the current `response`.
get()
Access specific elements in the design matrix or response data of the object.
steepAscent.c$get(i, j)
i
An integer specifying the row index to retrieve.
j
An integer specifying the column index to retrieve.
plot()
Plot the results of the steepest ascent procedure for an object of class `steepAscent.c`.
steepAscent.c$plot(main, xlab, ylab, l.col, p.col, line.type, point.shape)
main
The main title of the plot.
xlab
The label for the x-axis.
ylab
The label for the y-axis.
l.col
Color for the line in the plot.
p.col
Color for the points in the plot.
line.type
Type of the line used in the plot.
point.shape
Shape of the points used in the plot.
clone()
The objects of this class are cloneable with this method.
steepAscent.c$clone(deep = FALSE)
deep
Whether to make a deep clone.
steepAscent
, desirability.c
, optimum