# comp.kerncontour: Contour plot of the kernel density estimate in S^2 In Compositional: Compositional Data Analysis

 Contour plot of the kernel density estimate in S^2 R Documentation

## Contour plot of the kernel density estimate in S^2

### Description

Contour plot of the kernel density estimate in S^2.

### Usage

```comp.kerncontour(x, type = "alr", n = 50, cont.line = FALSE)
```

### Arguments

 `x` A matrix with the compositional data. It has to be a 3 column matrix. `type` This is either "alr" or "ilr", corresponding to the additive and the isometric log-ratio transformation respectively. `n` The number of grid points to consider, over which the density is calculated. `cont.line` Do you want the contour lines to appear? If yes, set this TRUE.

### Details

The alr or the ilr transformation are applied to the compositional data. Then, the optimal bandwidth using maximum likelihood cross-validation is chosen. The multivariate normal kernel density is calculated for a grid of points. Those points are the points on the 2-dimensional simplex. Finally the contours are plotted.

### Value

A ternary diagram with the points and the kernel contour lines.

### References

M.P. Wand and M.C. Jones (1995). Kernel smoothing, CrC Press.

Aitchison J. (1986). The statistical analysis of compositional data. Chapman & Hall.

```diri.contour, mix.compnorm.contour, bivt.contour, compnorm.contour ```

### Examples

```x <- as.matrix(iris[, 1:3])
x <- x / rowSums(x)
comp.kerncontour(x, type = "alr", n = 20)
comp.kerncontour(x, type = "ilr", n = 20)
```

Compositional documentation built on July 8, 2022, 1:06 a.m.