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.
nameA character string representing the name of the steep ascent design.
XA data frame containing the design matrix for the steepest ascent procedure. This matrix represents the factors and their levels at each iteration.
responseA 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$.response(value)valueA data frame or numeric vector to set as the new `response`. If missing, returns the current `response`.
get()Access specific elements in the design matrix or response data of the object.
steepAscent.c$get(i, j)iAn integer specifying the row index to retrieve.
jAn 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$plot(main, xlab, ylab, l.col, p.col, line.type, point.shape)mainThe main title of the plot.
xlabThe label for the x-axis.
ylabThe label for the y-axis.
l.colColor for the line in the plot.
p.colColor for the points in the plot.
line.typeType of the line used in the plot.
point.shapeShape of the points used in the plot.
clone()The objects of this class are cloneable with this method.
steepAscent.c$clone(deep = FALSE)deepWhether to make a deep clone.
steepAscent, desirability.c, optimum