plot.cv.compCL {Compack} R Documentation

## Plot the cross-validation curve produced by `"cv.compCL"` object.

### Description

Plot the cross-validation curve with its upper and lower standard deviation curves.

### Usage

```## S3 method for class 'cv.compCL'
plot(x, xlab = c("log", "-log", "lambda"), trim = FALSE, ...)
```

### Arguments

 `x` fitted `"cv.compCL"` object. `xlab` what is on the X-axis, `"log"` plots against `log(lambda)` (default), `"-log"` against `-log(lambda)`, and `"lambda"` against `lambda`. `trim` logical; whether to use the trimmed result. Default is `FALSE`. `...` other graphical parameters.

### Details

A cross-validation curve is produced.

### Value

No return value. Side effect is a base R plot.

### Author(s)

Zhe Sun and Kun Chen

### References

Lin, W., Shi, P., Peng, R. and Li, H. (2014) Variable selection in regression with compositional covariates, https://academic.oup.com/biomet/article/101/4/785/1775476. Biometrika 101 785-979.

`cv.compCL` and `compCL`, and `coef` and `plot` methods for `"cv.compCL"` object.

### Examples

```p = 30
n = 50
beta = c(1, -0.8, 0.6, 0, 0, -1.5, -0.5, 1.2)
beta = c(beta, rep(0, times = p - length(beta)))
Comp_data = comp_Model(n = n, p = p, intercept = FALSE)
cvm1 <- cv.compCL(y = Comp_data\$y, Z = Comp_data\$X.comp,
Zc = Comp_data\$Zc, intercept = Comp_data\$intercept)
plot(cvm1)
plot(cvm1, xlab = "-log")

```

[Package Compack version 0.1.0 Index]