# Component plot for repeated DCV of PRM

### Description

Generate plot showing optimal number of components for Repeated Double Cross-Validation of Partial Robust M-regression

### Usage

1 | ```
plotcompprm(prmdcvobj, ...)
``` |

### Arguments

`prmdcvobj` |
object from repeated double-CV of PRM, see |

`...` |
additional plot arguments |

### Details

After running repeated double-CV for PRM, this plot helps to decide on the final number of components.

### Value

`optcomp` |
optimal number of components |

`compdistrib` |
frequencies for the optimal number of components |

### Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

### References

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

### See Also

`prm`

### Examples

1 2 3 4 5 6 | ```
data(NIR)
X <- NIR$xNIR[1:30,] # first 30 observations - for illustration
y <- NIR$yGlcEtOH[1:30,1] # only variable Glucose
NIR.Glc <- data.frame(X=X, y=y)
res <- prm_dcv(X,y,a=4,repl=2)
plot2 <- plotcompprm(res)
``` |