GA_diagplot {RepeatedHighDim} | R Documentation |
Diagnostic plot for comparison of two correlation matrices.
Description
A diagnostic plot that compares the entries of two correlation matrices using a color scale.
Usage
GA_diagplot(
R,
Rt,
eps = 0.05,
col.method = "trafficlight",
color = c(0, 8),
top = ""
)
Arguments
R |
Specified correlation matrix. |
Rt |
Correlation matrix of the data generated by the genetic algorithm. |
eps |
Permitted difference between the entries of two matrices. Must only be specified if col.method="trafficlight". |
col.method |
Method to use for color scaling the difference between the matrices. If method="trafficlight" only two colors are used, indicating whether the entries deviated at least by a difference of eps. If method="updown" a discrete gray scale is used. |
color |
Value of two color that are used if method="trafficlight" |
top |
Specifies the main title of the plot |
Details
A diagnostic plot that compares the entries of two correlation matrices using a color scale.
Author(s)
Jochen Kruppa, Klaus Jung
References
Kruppa, J., Lepenies, B., & Jung, K. (2018). A genetic algorithm for simulating correlated binary data from biomedical research. Computers in biology and medicine, 92, 1-8. doi:10.1016/j.compbiomed.2017.10.023
See Also
For more information, please refer to the package's documentation and the tutorial: https://software.klausjung-lab.de/.
Examples
## Not run:
R1 = diag(10)
X0 <- start_matrix(p=c(0.4, 0.2, 0.5, 0.15, 0.4, 0.35, 0.2, 0.25, 0.3, 0.4), k = 5000)
Xt <- iter_matrix(X0, R = diag(10), T = 10000, e.min = 0.00001)
GA_diagplot(R1, Rt = Xt$Rt, col.method = "trafficlight")
GA_diagplot(R1, Rt = Xt$Rt, col.method = "updown")
## End(Not run)