plot.dissimilarities {analogue} R Documentation

## Plots the distribution of extracted dissimilarities

### Description

Produces a plot of the distribution of the extracted dissimilarities and a reference normal distribution with comparable mean and sd.

### Usage

```## S3 method for class 'dissimilarities'
plot(x, prob = 0.05,
legend = TRUE, n.rnorm = 1e+05, col = "black",
col.ref = "red", lty = "solid", lty.quant = "dotted",
xlab = NULL, ylab = NULL, main = NULL, sub = NULL, ...)
```

### Arguments

 `x` an object of class `"dissimilarities"`. `prob` numeric; density probability defining the threshold for close modern analogues. `legend` logical; draw a legend on the plotted figure? `n.rnorm` numeric; number of random normal deviates for reference line. `col, col.ref` colours for the dissimilarity and reference density functions drawn. `lty, lty.quant` line types for the dissimilarity and reference density functions drawn. `xlab, ylab` character; x- and y-axis labels. `main, sub` character; main and subtitle for the plot. `...` graphical arguments passed to other graphics functions.

### Value

A plot on the currently active device.

### Author(s)

Gavin L. Simpson

`dissimilarities`

### Examples

```## Imbrie and Kipp example
data(ImbrieKipp)
data(SumSST)
data(V12.122)

## merge training and test set on columns
dat <- join(ImbrieKipp, V12.122, verbose = TRUE)

## extract the merged data sets and convert to proportions
ImbrieKipp <- dat[] / 100
V12.122 <- dat[] / 100

## analog matching between SWAPImbrie & Kipp and V12.122 core
ik.analog <- analog(ImbrieKipp, V12.122, method = "chord")
ik.analog
summary(ik.analog)

## compare training set dissimilarities with normals
## and derive cut-offs
ik.dij <- dissim(ik.analog)
plot(ik.dij)
```

[Package analogue version 0.17-6 Index]