steepAscent.c {r6qualitytools} | R Documentation |
steepAscent-class: Class 'steepAscent'
Description
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.
Public fields
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.
Methods
Public methods
Method .response()
Get and set the 'response' values in an object of class 'steepAscent.c'.
Usage
steepAscent.c$.response(value)
Arguments
value
A data frame or numeric vector to set as the new 'response'. If missing, returns the current 'response'.
Method get()
Access specific elements in the design matrix or response data of the object.
Usage
steepAscent.c$get(i, j)
Arguments
i
An integer specifying the row index to retrieve.
j
An integer specifying the column index to retrieve.
Method as.data.frame()
Convert the object to a data frame.
Usage
steepAscent.c$as.data.frame()
Method print()
Print the details of the object.
Usage
steepAscent.c$print()
Method plot()
Plot the results of the steepest ascent procedure for an object of class 'steepAscent.c'.
Usage
steepAscent.c$plot(main, xlab, ylab, l.col, p.col, line.type, point.shape)
Arguments
main
The main title of the plot.
xlab
The label for the x-axis.
ylab
The label for the y-axis.
l.col
Color for the line in the plot.
p.col
Color for the points in the plot.
line.type
Type of the line used in the plot.
point.shape
Shape of the points used in the plot.
Method clone()
The objects of this class are cloneable with this method.
Usage
steepAscent.c$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
See Also
steepAscent
, desirability.c
, optimum